Session 10: Data Science Capstone Project
Maximilian Stock
2021-12-24
1 Introduction and learning objectives
2 Load data
There are two sets of data, i) training data that has the actual prices ii) out of sample data that has the asking prices. Load both data sets.
Make sure you understand what information each column contains. Note that not all information provided might be useful in predicting house prices, but do not make any assumptions before you decide what information you use in your prediction algorithms.
#read in the data
london_house_prices_2019_training<-read.csv("training_data_assignment_with_prices.csv")
london_house_prices_2019_out_of_sample<-read.csv("test_data_assignment.csv")
#fix data types in both data sets
#fix dates
london_house_prices_2019_training <- london_house_prices_2019_training %>% mutate(date=as.Date(date))
london_house_prices_2019_out_of_sample<-london_house_prices_2019_out_of_sample %>% mutate(date=as.Date(date))
#change characters to factors
london_house_prices_2019_training <- london_house_prices_2019_training %>% mutate_if(is.character,as.factor)
london_house_prices_2019_out_of_sample<-london_house_prices_2019_out_of_sample %>% mutate_if(is.character,as.factor)
#take a quick look at what's in the data
str(london_house_prices_2019_training)## 'data.frame': 13998 obs. of 37 variables:
## $ ID : int 2 3 4 5 7 8 9 10 11 12 ...
## $ date : Date, format: "2019-11-01" "2019-08-08" ...
## $ postcode : Factor w/ 12635 levels "BR1 1AB","BR1 1LR",..: 10897 11027 11264 2031 11241 11066 421 9594 9444 873 ...
## $ property_type : Factor w/ 4 levels "D","F","S","T": 2 2 3 2 3 2 1 4 4 2 ...
## $ whether_old_or_new : Factor w/ 2 levels "N","Y": 1 1 1 1 1 1 1 1 1 1 ...
## $ freehold_or_leasehold : Factor w/ 2 levels "F","L": 2 2 1 2 1 2 1 1 1 2 ...
## $ address1 : Factor w/ 2825 levels "1","1 - 2","1 - 3",..: 2503 792 253 789 569 234 264 418 5 274 ...
## $ address2 : Factor w/ 434 levels "1","10","101",..: 372 NA NA NA NA NA NA NA NA NA ...
## $ address3 : Factor w/ 8543 levels "ABBERTON WALK",..: 6990 6821 3715 2492 4168 2879 3620 5251 6045 6892 ...
## $ town : Factor w/ 133 levels "ABBEY WOOD","ACTON",..: NA NA NA 78 NA NA NA NA NA NA ...
## $ local_aut : Factor w/ 69 levels "ASHFORD","BARKING",..: 36 46 24 36 24 46 65 36 36 17 ...
## $ county : Factor w/ 33 levels "BARKING AND DAGENHAM",..: 22 27 18 25 18 27 5 27 32 8 ...
## $ postcode_short : Factor w/ 247 levels "BR1","BR2","BR3",..: 190 194 198 28 198 194 4 169 167 8 ...
## $ current_energy_rating : Factor w/ 6 levels "B","C","D","E",..: 4 3 3 4 3 2 4 3 4 2 ...
## $ total_floor_area : num 30 50 100 39 88 101 136 148 186 65 ...
## $ number_habitable_rooms : int 2 2 5 2 4 4 6 6 6 3 ...
## $ co2_emissions_current : num 2.3 3 3.7 2.8 3.9 3.1 8.1 5.6 10 1.5 ...
## $ co2_emissions_potential : num 1.7 1.7 1.5 1.1 1.4 1.4 4.1 2 6.1 1.5 ...
## $ energy_consumption_current : int 463 313 212 374 251 175 339 216 308 128 ...
## $ energy_consumption_potential: int 344 175 82 144 90 77 168 75 186 128 ...
## $ windows_energy_eff : Factor w/ 5 levels "Average","Good",..: 1 1 1 5 1 1 1 1 5 1 ...
## $ tenure : Factor w/ 3 levels "owner-occupied",..: 1 2 1 2 1 1 1 2 1 1 ...
## $ latitude : num 51.5 51.5 51.5 51.6 51.5 ...
## $ longitude : num -0.1229 -0.2828 -0.4315 0.0423 -0.4293 ...
## $ population : int 34 75 83 211 73 51 25 91 60 97 ...
## $ altitude : int 8 9 25 11 21 11 95 7 7 106 ...
## $ london_zone : int 1 3 5 3 6 6 3 2 2 3 ...
## $ nearest_station : Factor w/ 592 levels "abbey road","abbey wood",..: 478 358 235 319 180 502 566 30 32 566 ...
## $ water_company : Factor w/ 5 levels "Affinity Water",..: 5 5 1 5 1 5 5 5 5 5 ...
## $ average_income : int 57200 61900 50600 45400 49000 56200 57200 65600 50400 52300 ...
## $ district : Factor w/ 33 levels "Barking and Dagenham",..: 22 27 18 26 18 27 5 27 32 8 ...
## $ price : num 360000 408500 499950 259999 395000 ...
## $ type_of_closest_station : Factor w/ 3 levels "light_rail","rail",..: 3 2 3 1 3 2 1 3 1 1 ...
## $ num_tube_lines : int 1 0 1 0 1 0 0 2 0 0 ...
## $ num_rail_lines : int 0 1 1 0 1 1 0 0 1 0 ...
## $ num_light_rail_lines : int 0 0 0 1 0 0 1 0 1 1 ...
## $ distance_to_station : num 0.528 0.77 0.853 0.29 1.073 ...str(london_house_prices_2019_out_of_sample)## 'data.frame': 1999 obs. of 37 variables:
## $ ID : int 14434 12562 8866 10721 1057 1527 13961 12108 9363 1155 ...
## $ date : Date, format: NA NA ...
## $ postcode : logi NA NA NA NA NA NA ...
## $ property_type : Factor w/ 4 levels "D","F","S","T": 1 2 2 3 4 3 2 3 2 4 ...
## $ whether_old_or_new : Factor w/ 2 levels "N","Y": 1 1 1 1 1 1 1 1 1 1 ...
## $ freehold_or_leasehold : Factor w/ 2 levels "F","L": 1 2 2 1 1 1 2 1 2 1 ...
## $ address1 : logi NA NA NA NA NA NA ...
## $ address2 : logi NA NA NA NA NA NA ...
## $ address3 : logi NA NA NA NA NA NA ...
## $ town : Factor w/ 54 levels "ACTON","ADDISCOMBE",..: NA NA NA NA NA NA NA NA NA NA ...
## $ local_aut : logi NA NA NA NA NA NA ...
## $ county : logi NA NA NA NA NA NA ...
## $ postcode_short : Factor w/ 221 levels "BR1","BR2","BR3",..: 82 50 37 52 214 150 159 115 175 126 ...
## $ current_energy_rating : Factor w/ 6 levels "B","C","D","E",..: 3 2 3 3 4 4 4 3 4 3 ...
## $ total_floor_area : num 150 59 58 74 97.3 ...
## $ number_habitable_rooms : int 6 2 2 5 5 5 5 4 2 5 ...
## $ co2_emissions_current : num 7.3 1.5 2.8 3.5 6.5 4.9 5.1 2.9 4.2 4.3 ...
## $ co2_emissions_potential : num 2.4 1.4 1.2 1.2 5.7 1.6 3 0.8 3.2 2.5 ...
## $ energy_consumption_current : int 274 142 253 256 303 309 240 224 458 253 ...
## $ energy_consumption_potential: int 89 136 110 80 266 101 140 58 357 143 ...
## $ windows_energy_eff : Factor w/ 5 levels "Average","Good",..: 1 1 1 1 1 1 3 1 3 1 ...
## $ tenure : Factor w/ 3 levels "owner-occupied",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ latitude : num 51.6 51.6 51.5 51.6 51.5 ...
## $ longitude : num -0.129 -0.2966 -0.0328 -0.3744 -0.2576 ...
## $ population : int 87 79 23 73 100 24 22 49 65 98 ...
## $ altitude : int 63 38 17 39 8 46 26 16 14 18 ...
## $ london_zone : int 4 4 2 5 2 4 3 6 1 3 ...
## $ nearest_station : Factor w/ 494 levels "abbey wood","acton central",..: 16 454 181 302 431 142 20 434 122 212 ...
## $ water_company : Factor w/ 4 levels "Affinity Water",..: 4 1 4 1 4 4 4 2 4 4 ...
## $ average_income : int 61300 48900 46200 52200 60700 59600 64000 48100 56600 53500 ...
## $ district : Factor w/ 32 levels "Barking and Dagenham",..: 9 4 29 14 17 10 31 15 19 22 ...
## $ type_of_closest_station : Factor w/ 3 levels "light_rail","rail",..: 3 3 1 2 3 2 3 3 3 2 ...
## $ num_tube_lines : int 1 2 0 0 2 0 1 1 2 0 ...
## $ num_rail_lines : int 0 1 0 1 0 1 1 0 0 1 ...
## $ num_light_rail_lines : int 0 1 1 0 0 0 0 1 0 0 ...
## $ distance_to_station : num 0.839 0.104 0.914 0.766 0.449 ...
## $ asking_price : num 750000 229000 152000 379000 930000 350000 688000 386000 534000 459000 ...set.seed(2999)
#let's do the initial split
train_test_split <- initial_split(london_house_prices_2019_training, prop = 0.75) #training set contains 75% of the data
# Create the training dataset
train_data <- training(train_test_split)
test_data <- testing(train_test_split)3 Visualize data
Visualize and examine the data. What plots could be useful here? What do you learn from these visualizations?
plotData <- london_house_prices_2019_training %>%
group_by(date) %>%
summarise(medianPrice = median(price))
ggplot(plotData, aes(x = date, y = medianPrice)) +
geom_line(colour = "steelblue") +
geom_point() +
geom_smooth() +
scale_y_continuous(labels = number) +
theme_bw() +
labs(x = "Date", y = "Daily Median Sales Price in GBP")## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
There seems to be a slight seasonality in daily meadian house prices, with the summer being higher. However, this increase does not seem too drastic.
ggplot(london_house_prices_2019_training, aes(x = price)) +
geom_density(color = "steelblue") +
scale_y_continuous(labels = percent) +
scale_x_continuous(labels = number) +
theme_bw() +
labs(x = "Price in GBP", y = "Distribution")
House prices are heaviliy skewed to the right. This indicates that there are large outlying values. We should assess the impact of this on our models.
Estimate a correlation table between prices and other continuous variables. What do you glean from the correlation table?
A first idea about potential relations in the data as well as potential drivers of our dependent price variable.
# produce a correlation table using GGally::ggcorr()
# this takes a while to plot
london_house_prices_2019_training %>%
select(-ID) %>% #keep Y variable last
ggcorr(method = c("pairwise", "pearson"), layout.exp = 2,label_round=2, label = TRUE,label_size = 2,hjust = 1,nbreaks = 5,size = 2) +
theme_bw()
4 Fit a linear regression model
#Define control variables
lrControl <- trainControl (
method="cv",
number=5,
verboseIter=FALSE) #by setting this to FALSE the model will not report its progress after each estimation
#we are going to train the model and report the results using k-fold cross validation
model1_lm<-train(
price ~ district*total_floor_area + london_zone*number_habitable_rooms + co2_emissions_potential + distance_to_station +water_company+property_type+latitude+ longitude + average_income + property_type,
train_data,
method = "lm",
trControl = lrControl
)
# summary of the results
summary(model1_lm)##
## Call:
## lm(formula = .outcome ~ ., data = dat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3293917 -70924 -958 65630 4420578
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) -7.974e+06 5.882e+06 -1.356
## districtBarnet -1.185e+05 6.256e+04 -1.895
## districtBexley -1.044e+05 6.336e+04 -1.647
## districtBrent -1.893e+05 6.649e+04 -2.847
## districtBromley -1.094e+05 6.160e+04 -1.776
## districtCamden -3.438e+05 6.364e+04 -5.402
## `districtCity of London` -5.747e+05 1.936e+05 -2.968
## districtCroydon -3.427e+04 6.245e+04 -0.549
## districtEaling -8.515e+04 6.720e+04 -1.267
## districtEnfield -2.595e+04 6.315e+04 -0.411
## districtGreenwich -1.774e+05 6.261e+04 -2.833
## districtHackney -1.823e+05 6.470e+04 -2.817
## `districtHammersmith and Fulham` -3.306e+05 6.838e+04 -4.835
## districtHaringey -2.025e+05 6.711e+04 -3.018
## districtHarrow 5.428e+04 7.279e+04 0.746
## districtHavering 9.842e+03 5.891e+04 0.167
## districtHillingdon 1.055e+05 7.121e+04 1.481
## districtHounslow -1.696e+05 7.149e+04 -2.373
## districtIslington -3.711e+05 6.736e+04 -5.509
## `districtKensington and Chelsea` -6.229e+05 6.615e+04 -9.417
## `districtKingston upon Thames` -1.023e+05 6.656e+04 -1.536
## districtLambeth -2.391e+05 6.483e+04 -3.688
## districtLewisham -1.165e+05 6.362e+04 -1.830
## districtMerton -3.036e+05 6.563e+04 -4.625
## districtNewham -1.133e+05 7.367e+04 -1.538
## districtRedbridge -1.162e+05 5.829e+04 -1.994
## `districtRichmond upon Thames` -2.257e+05 6.689e+04 -3.375
## districtSouthwark -2.366e+05 6.372e+04 -3.712
## districtSutton -5.012e+04 6.734e+04 -0.744
## `districtTower Hamlets` -2.664e+05 6.970e+04 -3.822
## `districtWaltham Forest` -5.270e+04 6.605e+04 -0.798
## districtWandsworth -2.214e+05 6.413e+04 -3.452
## districtWestminster -8.278e+05 6.732e+04 -12.296
## total_floor_area 2.365e+03 6.286e+02 3.762
## london_zone -2.927e+04 6.179e+03 -4.736
## number_habitable_rooms 9.204e+03 5.463e+03 1.685
## co2_emissions_potential 2.004e+04 1.952e+03 10.265
## distance_to_station -1.463e+04 5.992e+03 -2.442
## `water_companyEssex & Suffolk Water` -1.002e+04 2.684e+04 -0.373
## `water_companyLeep Utilities` 8.071e+04 1.242e+05 0.650
## `water_companySES Water` 6.685e+04 2.231e+04 2.996
## `water_companyThames Water` 4.638e+04 1.484e+04 3.126
## property_typeF -2.224e+05 1.229e+04 -18.090
## property_typeS -1.121e+05 1.070e+04 -10.474
## property_typeT -1.379e+05 1.102e+04 -12.512
## latitude 1.572e+05 1.139e+05 1.380
## longitude 2.996e+05 6.928e+04 4.324
## average_income 7.198e+00 3.177e-01 22.655
## `districtBarnet:total_floor_area` 2.955e+03 6.456e+02 4.577
## `districtBexley:total_floor_area` 6.191e+02 6.924e+02 0.894
## `districtBrent:total_floor_area` 4.413e+03 6.779e+02 6.509
## `districtBromley:total_floor_area` 1.196e+03 6.518e+02 1.835
## `districtCamden:total_floor_area` 7.377e+03 6.630e+02 11.125
## `districtCity of London:total_floor_area` 1.383e+04 3.144e+03 4.398
## `districtCroydon:total_floor_area` 3.160e+02 6.492e+02 0.487
## `districtEaling:total_floor_area` 2.870e+03 6.712e+02 4.276
## `districtEnfield:total_floor_area` 1.013e+03 6.764e+02 1.497
## `districtGreenwich:total_floor_area` 1.711e+03 6.790e+02 2.520
## `districtHackney:total_floor_area` 3.889e+03 7.008e+02 5.549
## `districtHammersmith and Fulham:total_floor_area` 7.547e+03 6.742e+02 11.194
## `districtHaringey:total_floor_area` 3.790e+03 7.079e+02 5.354
## `districtHarrow:total_floor_area` 1.522e+03 7.066e+02 2.154
## `districtHavering:total_floor_area` 3.929e+02 6.875e+02 0.571
## `districtHillingdon:total_floor_area` 1.448e+03 6.946e+02 2.085
## `districtHounslow:total_floor_area` 4.411e+03 7.071e+02 6.237
## `districtIslington:total_floor_area` 7.147e+03 7.230e+02 9.885
## `districtKensington and Chelsea:total_floor_area` 1.648e+04 6.619e+02 24.899
## `districtKingston upon Thames:total_floor_area` 3.190e+03 6.569e+02 4.856
## `districtLambeth:total_floor_area` 4.166e+03 6.783e+02 6.142
## `districtLewisham:total_floor_area` 1.122e+03 6.842e+02 1.640
## `districtMerton:total_floor_area` 4.557e+03 6.725e+02 6.776
## `districtNewham:total_floor_area` 5.436e+02 8.322e+02 0.653
## `districtRedbridge:total_floor_area` 1.099e+03 6.658e+02 1.650
## `districtRichmond upon Thames:total_floor_area` 5.570e+03 6.508e+02 8.559
## `districtSouthwark:total_floor_area` 4.162e+03 6.857e+02 6.070
## `districtSutton:total_floor_area` 8.412e+02 6.804e+02 1.236
## `districtTower Hamlets:total_floor_area` 3.459e+03 7.908e+02 4.374
## `districtWaltham Forest:total_floor_area` 1.031e+03 7.426e+02 1.388
## `districtWandsworth:total_floor_area` 4.373e+03 6.600e+02 6.625
## `districtWestminster:total_floor_area` 1.659e+04 6.876e+02 24.120
## `london_zone:number_habitable_rooms` -5.964e+03 1.248e+03 -4.778
## Pr(>|t|)
## (Intercept) 0.175230
## districtBarnet 0.058183 .
## districtBexley 0.099549 .
## districtBrent 0.004418 **
## districtBromley 0.075719 .
## districtCamden 6.74e-08 ***
## `districtCity of London` 0.003004 **
## districtCroydon 0.583127
## districtEaling 0.205171
## districtEnfield 0.681090
## districtGreenwich 0.004613 **
## districtHackney 0.004850 **
## `districtHammersmith and Fulham` 1.35e-06 ***
## districtHaringey 0.002553 **
## districtHarrow 0.455872
## districtHavering 0.867317
## districtHillingdon 0.138609
## districtHounslow 0.017668 *
## districtIslington 3.70e-08 ***
## `districtKensington and Chelsea` < 2e-16 ***
## `districtKingston upon Thames` 0.124448
## districtLambeth 0.000227 ***
## districtLewisham 0.067204 .
## districtMerton 3.79e-06 ***
## districtNewham 0.124027
## districtRedbridge 0.046214 *
## `districtRichmond upon Thames` 0.000742 ***
## districtSouthwark 0.000206 ***
## districtSutton 0.456776
## `districtTower Hamlets` 0.000133 ***
## `districtWaltham Forest` 0.424926
## districtWandsworth 0.000560 ***
## districtWestminster < 2e-16 ***
## total_floor_area 0.000170 ***
## london_zone 2.21e-06 ***
## number_habitable_rooms 0.092040 .
## co2_emissions_potential < 2e-16 ***
## distance_to_station 0.014605 *
## `water_companyEssex & Suffolk Water` 0.708879
## `water_companyLeep Utilities` 0.515841
## `water_companySES Water` 0.002738 **
## `water_companyThames Water` 0.001777 **
## property_typeF < 2e-16 ***
## property_typeS < 2e-16 ***
## property_typeT < 2e-16 ***
## latitude 0.167614
## longitude 1.55e-05 ***
## average_income < 2e-16 ***
## `districtBarnet:total_floor_area` 4.77e-06 ***
## `districtBexley:total_floor_area` 0.371272
## `districtBrent:total_floor_area` 7.89e-11 ***
## `districtBromley:total_floor_area` 0.066463 .
## `districtCamden:total_floor_area` < 2e-16 ***
## `districtCity of London:total_floor_area` 1.10e-05 ***
## `districtCroydon:total_floor_area` 0.626391
## `districtEaling:total_floor_area` 1.92e-05 ***
## `districtEnfield:total_floor_area` 0.134354
## `districtGreenwich:total_floor_area` 0.011760 *
## `districtHackney:total_floor_area` 2.94e-08 ***
## `districtHammersmith and Fulham:total_floor_area` < 2e-16 ***
## `districtHaringey:total_floor_area` 8.79e-08 ***
## `districtHarrow:total_floor_area` 0.031279 *
## `districtHavering:total_floor_area` 0.567675
## `districtHillingdon:total_floor_area` 0.037119 *
## `districtHounslow:total_floor_area` 4.62e-10 ***
## `districtIslington:total_floor_area` < 2e-16 ***
## `districtKensington and Chelsea:total_floor_area` < 2e-16 ***
## `districtKingston upon Thames:total_floor_area` 1.21e-06 ***
## `districtLambeth:total_floor_area` 8.47e-10 ***
## `districtLewisham:total_floor_area` 0.100940
## `districtMerton:total_floor_area` 1.31e-11 ***
## `districtNewham:total_floor_area` 0.513655
## `districtRedbridge:total_floor_area` 0.098907 .
## `districtRichmond upon Thames:total_floor_area` < 2e-16 ***
## `districtSouthwark:total_floor_area` 1.32e-09 ***
## `districtSutton:total_floor_area` 0.216370
## `districtTower Hamlets:total_floor_area` 1.23e-05 ***
## `districtWaltham Forest:total_floor_area` 0.165203
## `districtWandsworth:total_floor_area` 3.64e-11 ***
## `districtWestminster:total_floor_area` < 2e-16 ***
## `london_zone:number_habitable_rooms` 1.79e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 213000 on 10417 degrees of freedom
## Multiple R-squared: 0.8286, Adjusted R-squared: 0.8273
## F-statistic: 629.4 on 80 and 10417 DF, p-value: < 2.2e-16We have also seen how there are large outlying values in our response price variable.
#untransformed price variable
plot(lm(price ~ district*total_floor_area + london_zone*number_habitable_rooms + co2_emissions_potential + distance_to_station +water_company+property_type+latitude+ longitude + average_income + property_type,
train_data))
#transformed price variable
plot(lm(log(price) ~ district*total_floor_area + london_zone*number_habitable_rooms + co2_emissions_potential + distance_to_station +water_company+property_type+latitude+ longitude + average_income + property_type,
train_data))
In the above Plots, we can identify how residuals at extreme quartile ends diverge from normality. Let us therefore see how the performance of our linear regression changes when we do a log transformation of price.
#building log transformed price linear regression
model1_lm_log<-train(
log(price) ~ district*total_floor_area + london_zone*number_habitable_rooms + co2_emissions_potential + distance_to_station +water_company+property_type+latitude+ longitude + average_income + property_type,
train_data,
method = "lm",
trControl = lrControl
)
summary(model1_lm_log)##
## Call:
## lm(formula = .outcome ~ ., data = dat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.52621 -0.11739 0.00723 0.13613 1.27259
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) -9.068e+00 6.487e+00 -1.398
## districtBarnet 2.459e-01 6.900e-02 3.563
## districtBexley -5.664e-02 6.987e-02 -0.811
## districtBrent 1.237e-01 7.332e-02 1.687
## districtBromley 1.318e-02 6.793e-02 0.194
## districtCamden 3.782e-01 7.018e-02 5.389
## `districtCity of London` -1.969e-01 2.135e-01 -0.922
## districtCroydon 1.025e-01 6.887e-02 1.489
## districtEaling 1.771e-01 7.411e-02 2.390
## districtEnfield 1.628e-01 6.964e-02 2.337
## districtGreenwich -1.496e-02 6.905e-02 -0.217
## districtHackney 2.014e-01 7.136e-02 2.823
## `districtHammersmith and Fulham` 3.366e-01 7.541e-02 4.463
## districtHaringey 1.685e-01 7.401e-02 2.277
## districtHarrow 2.451e-01 8.027e-02 3.053
## districtHavering 1.940e-01 6.497e-02 2.987
## districtHillingdon 2.477e-01 7.853e-02 3.154
## districtHounslow 7.712e-02 7.884e-02 0.978
## districtIslington 1.046e-01 7.428e-02 1.408
## `districtKensington and Chelsea` 5.616e-01 7.295e-02 7.698
## `districtKingston upon Thames` 2.149e-01 7.341e-02 2.928
## districtLambeth 2.521e-01 7.149e-02 3.526
## districtLewisham -5.475e-03 7.016e-02 -0.078
## districtMerton 9.987e-03 7.238e-02 0.138
## districtNewham -1.068e-01 8.124e-02 -1.314
## districtRedbridge 4.255e-02 6.428e-02 0.662
## `districtRichmond upon Thames` 3.013e-01 7.377e-02 4.084
## districtSouthwark 1.499e-01 7.028e-02 2.133
## districtSutton 8.435e-03 7.427e-02 0.114
## `districtTower Hamlets` -1.114e-01 7.686e-02 -1.449
## `districtWaltham Forest` 1.615e-01 7.284e-02 2.217
## districtWandsworth 1.924e-01 7.072e-02 2.720
## districtWestminster 3.461e-01 7.424e-02 4.662
## total_floor_area 5.157e-03 6.932e-04 7.439
## london_zone -8.825e-02 6.815e-03 -12.950
## number_habitable_rooms 2.304e-02 6.024e-03 3.824
## co2_emissions_potential 6.681e-03 2.152e-03 3.104
## distance_to_station -3.387e-02 6.608e-03 -5.126
## `water_companyEssex & Suffolk Water` 1.867e-02 2.960e-02 0.631
## `water_companyLeep Utilities` 2.586e-01 1.370e-01 1.888
## `water_companySES Water` 1.516e-01 2.460e-02 6.164
## `water_companyThames Water` 1.413e-01 1.636e-02 8.639
## property_typeF -4.116e-01 1.356e-02 -30.361
## property_typeS -9.513e-02 1.180e-02 -8.058
## property_typeT -1.531e-01 1.215e-02 -12.593
## latitude 4.111e-01 1.257e-01 3.272
## longitude 8.379e-02 7.641e-02 1.097
## average_income 1.319e-05 3.504e-07 37.645
## `districtBarnet:total_floor_area` -2.981e-04 7.120e-04 -0.419
## `districtBexley:total_floor_area` -2.817e-04 7.636e-04 -0.369
## `districtBrent:total_floor_area` 1.264e-03 7.476e-04 1.690
## `districtBromley:total_floor_area` 5.831e-06 7.188e-04 0.008
## `districtCamden:total_floor_area` 5.293e-04 7.312e-04 0.724
## `districtCity of London:total_floor_area` 1.085e-02 3.468e-03 3.128
## `districtCroydon:total_floor_area` -1.393e-03 7.159e-04 -1.945
## `districtEaling:total_floor_area` -1.777e-04 7.402e-04 -0.240
## `districtEnfield:total_floor_area` -1.200e-03 7.459e-04 -1.609
## `districtGreenwich:total_floor_area` -2.338e-05 7.488e-04 -0.031
## `districtHackney:total_floor_area` 9.761e-04 7.729e-04 1.263
## `districtHammersmith and Fulham:total_floor_area` 1.121e-03 7.435e-04 1.507
## `districtHaringey:total_floor_area` 3.242e-04 7.807e-04 0.415
## `districtHarrow:total_floor_area` -2.923e-04 7.792e-04 -0.375
## `districtHavering:total_floor_area` -9.168e-04 7.582e-04 -1.209
## `districtHillingdon:total_floor_area` -3.094e-04 7.661e-04 -0.404
## `districtHounslow:total_floor_area` 1.183e-03 7.798e-04 1.517
## `districtIslington:total_floor_area` 2.807e-03 7.974e-04 3.521
## `districtKensington and Chelsea:total_floor_area` 2.408e-03 7.299e-04 3.299
## `districtKingston upon Thames:total_floor_area` -1.472e-04 7.244e-04 -0.203
## `districtLambeth:total_floor_area` -3.347e-04 7.481e-04 -0.447
## `districtLewisham:total_floor_area` 1.786e-04 7.546e-04 0.237
## `districtMerton:total_floor_area` 7.302e-04 7.416e-04 0.985
## `districtNewham:total_floor_area` -4.339e-05 9.178e-04 -0.047
## `districtRedbridge:total_floor_area` -5.857e-04 7.342e-04 -0.798
## `districtRichmond upon Thames:total_floor_area` 2.246e-04 7.177e-04 0.313
## `districtSouthwark:total_floor_area` 9.492e-04 7.562e-04 1.255
## `districtSutton:total_floor_area` -4.311e-04 7.503e-04 -0.575
## `districtTower Hamlets:total_floor_area` 2.900e-03 8.721e-04 3.326
## `districtWaltham Forest:total_floor_area` -8.867e-04 8.190e-04 -1.083
## `districtWandsworth:total_floor_area` 6.087e-04 7.278e-04 0.836
## `districtWestminster:total_floor_area` 3.761e-03 7.583e-04 4.960
## `london_zone:number_habitable_rooms` 1.538e-03 1.376e-03 1.117
## Pr(>|t|)
## (Intercept) 0.162161
## districtBarnet 0.000368 ***
## districtBexley 0.417633
## districtBrent 0.091690 .
## districtBromley 0.846194
## districtCamden 7.26e-08 ***
## `districtCity of London` 0.356419
## districtCroydon 0.136503
## districtEaling 0.016879 *
## districtEnfield 0.019442 *
## districtGreenwich 0.828517
## districtHackney 0.004766 **
## `districtHammersmith and Fulham` 8.16e-06 ***
## districtHaringey 0.022819 *
## districtHarrow 0.002274 **
## districtHavering 0.002826 **
## districtHillingdon 0.001614 **
## districtHounslow 0.328011
## districtIslington 0.159177
## `districtKensington and Chelsea` 1.51e-14 ***
## `districtKingston upon Thames` 0.003417 **
## districtLambeth 0.000424 ***
## districtLewisham 0.937803
## districtMerton 0.890260
## districtNewham 0.188763
## districtRedbridge 0.508002
## `districtRichmond upon Thames` 4.45e-05 ***
## districtSouthwark 0.032973 *
## districtSutton 0.909579
## `districtTower Hamlets` 0.147291
## `districtWaltham Forest` 0.026625 *
## districtWandsworth 0.006536 **
## districtWestminster 3.17e-06 ***
## total_floor_area 1.09e-13 ***
## london_zone < 2e-16 ***
## number_habitable_rooms 0.000132 ***
## co2_emissions_potential 0.001914 **
## distance_to_station 3.01e-07 ***
## `water_companyEssex & Suffolk Water` 0.528136
## `water_companyLeep Utilities` 0.059032 .
## `water_companySES Water` 7.38e-10 ***
## `water_companyThames Water` < 2e-16 ***
## property_typeF < 2e-16 ***
## property_typeS 8.58e-16 ***
## property_typeT < 2e-16 ***
## latitude 0.001073 **
## longitude 0.272798
## average_income < 2e-16 ***
## `districtBarnet:total_floor_area` 0.675510
## `districtBexley:total_floor_area` 0.712157
## `districtBrent:total_floor_area` 0.091051 .
## `districtBromley:total_floor_area` 0.993527
## `districtCamden:total_floor_area` 0.469180
## `districtCity of London:total_floor_area` 0.001762 **
## `districtCroydon:total_floor_area` 0.051767 .
## `districtEaling:total_floor_area` 0.810323
## `districtEnfield:total_floor_area` 0.107730
## `districtGreenwich:total_floor_area` 0.975087
## `districtHackney:total_floor_area` 0.206630
## `districtHammersmith and Fulham:total_floor_area` 0.131819
## `districtHaringey:total_floor_area` 0.677927
## `districtHarrow:total_floor_area` 0.707549
## `districtHavering:total_floor_area` 0.226595
## `districtHillingdon:total_floor_area` 0.686321
## `districtHounslow:total_floor_area` 0.129343
## `districtIslington:total_floor_area` 0.000432 ***
## `districtKensington and Chelsea:total_floor_area` 0.000974 ***
## `districtKingston upon Thames:total_floor_area` 0.838982
## `districtLambeth:total_floor_area` 0.654574
## `districtLewisham:total_floor_area` 0.812904
## `districtMerton:total_floor_area` 0.324866
## `districtNewham:total_floor_area` 0.962294
## `districtRedbridge:total_floor_area` 0.425047
## `districtRichmond upon Thames:total_floor_area` 0.754290
## `districtSouthwark:total_floor_area` 0.209414
## `districtSutton:total_floor_area` 0.565597
## `districtTower Hamlets:total_floor_area` 0.000885 ***
## `districtWaltham Forest:total_floor_area` 0.278979
## `districtWandsworth:total_floor_area` 0.402972
## `districtWestminster:total_floor_area` 7.17e-07 ***
## `london_zone:number_habitable_rooms` 0.264011
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2349 on 10417 degrees of freedom
## Multiple R-squared: 0.8164, Adjusted R-squared: 0.815
## F-statistic: 579.1 on 80 and 10417 DF, p-value: < 2.2e-164.1 Predict the values in testing and out of sample data
Below I use the predict function to test the performance of the model in testing data and summarize the performance of the linear regression model. How can you measure the quality of your predictions?
We can assess the performance through 1) the fit of the model obtained through cross validation and 2) through out of sample testing and aiming for RMSE minimisation.
#results of untransformed price variable
lrPredictions <- predict(model1_lm,test_data)
lr_results<-data.frame( RMSE = RMSE(lrPredictions, test_data$price),
Rsquare = R2(lrPredictions, test_data$price))
lr_results ## RMSE Rsquare
## 1 204467.4 0.8570818#results of transformed price variable
loggedPredictions <- exp(predict(model1_lm_log,test_data))
logged_lr_results<-data.frame( RMSE = RMSE(loggedPredictions, test_data$price),
Rsquare = R2(loggedPredictions, test_data$price))
logged_lr_results ## RMSE Rsquare
## 1 615799.8 0.5978141As we can see, the log transformed model performs significantly worse, especially in out of sample testing. We therefore decide to stay with untransformed price as a response variable.
# we can check variable importance as well
importance <- varImp(model1_lm, scale=TRUE)
plot(importance)
train_data %>%
group_by(district) %>%
summarise(medianPrice = median(price)) %>%
ggplot(aes(x = medianPrice, y = fct_reorder(district, medianPrice))) +
geom_col(fill = "steelblue") +
theme_classic()
Comparing the above plot with the plot on variable importance, we can see that interaction variables are especially important between floor area and districts that have high median prices in housing. This lets us to hypothesise that floor area has specifically high leverage on a houses valuation when it is located in an upscale area.
5 Fit a tree model
modelLookup("rpart") #To mitigate decision trees’ shortcomings, the introduction of a complexity parameter cp and an associated cost function penalising a tree’s size can be useful. In the case at hand, an array of values for cp are iterated/tuned through and optimal values are found by cross validating RMSEs. As trees run the risk of overfitting as their size increases, this pruning measure allows for optimising variance.## model parameter label forReg forClass probModel
## 1 rpart cp Complexity Parameter TRUE TRUE TRUEtreeControl <- trainControl(
method="cv",
number=5,
verboseIter=FALSE)
treeGrid <- expand.grid(cp = seq(0.0000, 0.001,0.00001))
model2_tree <- train(
price ~ district*total_floor_area + london_zone + number_habitable_rooms + co2_emissions_potential + distance_to_station +water_company+property_type+latitude+ longitude + average_income,
train_data,
method = "rpart",
trControl = treeControl,
tuneLength=10,
tuneGrid = treeGrid
)
plot(model2_tree)
treeImportance <- varImp(model2_tree, scale=TRUE)
plot(treeImportance)
The plot on the complexity parameter against the cross validated RMSE performance nicely indicates the optimally tuned penalising parameter. It is furthermore interesting to see how variable importance gets is different to , which can possibly be attributed to trees susceptibility to over emphasise variables with large outlying values.
# We can predict the testing values
treePredictions <- predict(model2_tree,test_data)
tree_results<-data.frame( RMSE = RMSE(treePredictions, test_data$price),
Rsquare = R2(treePredictions, test_data$price))
tree_results ## RMSE Rsquare
## 1 257971.1 0.7706503One can argue that the poor OOS performance of the Regression Trees is caused by the algorithm’s tendency towards high variance. Applying this notion to the problem of predicting prices, it is likely that the presence of large outlying values in training sets heavily influences predictions to extreme degrees. Thus, this model is not considered viable for further analyses, especially because random forests represent an improvement to simpler regression trees.
6 Other algorithms
Use at least two other algorithms to predict prices. Don’t forget to tune the parameters of these algorithms. And then compare the performances of your algorithms to linear regression and trees.
modelLookup("svmRadial")## model parameter label forReg forClass probModel
## 1 svmRadial sigma Sigma TRUE TRUE TRUE
## 2 svmRadial C Cost TRUE TRUE TRUE# Tuning of C and Sigma is not done in a pre-specified grid fashion, but is left over to the algorithm to get a sense for the outcomes in a broader and less constrained way.
svmControl <- trainControl(method="cv", number=5, verboseIter = FALSE) #again, train controlling is done through cross validation
model3_svm <- train(
price ~ total_floor_area + district + london_zone + number_habitable_rooms + co2_emissions_potential + distance_to_station +water_company+property_type+latitude+ longitude + average_income,
train_data,
method = "svmRadial",
trControl = svmControl,
tuneLength = 10)
svmImportance <- varImp(model3_svm, scale=TRUE)
plot(svmImportance)
# lets also assess the out of sample performance of support vector regression
svmPredictions <- predict(model3_svm,test_data)
svm_results<-data.frame( RMSE = RMSE(svmPredictions, test_data$price),
Rsquare = R2(svmPredictions, test_data$price))
svm_results ## RMSE Rsquare
## 1 179665 0.8936471#next, we construct random forests
modelLookup("ranger")## model parameter label forReg forClass probModel
## 1 ranger mtry #Randomly Selected Predictors TRUE TRUE TRUE
## 2 ranger splitrule Splitting Rule TRUE TRUE TRUE
## 3 ranger min.node.size Minimal Node Size TRUE TRUE TRUErfControl <- trainControl(verboseIter = FALSE, method = "cv", number = 5)
# Tuning on mtry (number of predictors randomly sampled at each split), splitrule and min.node.size is not done in a pre-specified grid fashion, but is left over to the algorithm to get a sense for the outcomes in a broader and less constrained way.
model4_randomForests <- train(
price ~ total_floor_area + district + london_zone + number_habitable_rooms + co2_emissions_potential + distance_to_station +water_company+property_type+latitude+ longitude + average_income,
na.action = na.omit,
train_data,
method = "ranger",
trControl = rfControl
)#we also assess the out of sample performance of the constructed trees
rfPredictions <- predict(model4_randomForests,test_data)
rf_results<-data.frame( RMSE = RMSE(rfPredictions, test_data$price),
Rsquare = R2(rfPredictions, test_data$price))
rf_results## RMSE Rsquare
## 1 197243.4 0.871355#as a last algorithm, we engage in gradient boosting models
#lets tune the characteristics of the built trees
# tuning is mostly done to mitigate overfitting/variance by adjusting multiple parameters, especially through limiting n.tree (the number of trees/iterations) and interaction.depth (the number of nodes). At the heart of GBM is shrinkage, regularising the impact of additionally added trees to limit susceptibility to overfitting
gbmGrid <- expand.grid(interaction.depth=c(1, 3, 5), n.trees = (0:50)*50,shrinkage=c(0.01, 0.001), n.minobsinnode=10)
metricToMinimise <- "RMSE"
trainControl <- trainControl(method="cv", number=5, verboseIter = FALSE)
model5_gbm <- train(
price ~ total_floor_area + district + london_zone + number_habitable_rooms + co2_emissions_potential + distance_to_station +water_company+property_type+latitude+ longitude + average_income + property_type,
train_data,
distribution="gaussian",
method="gbm",
trControl=trainControl,
tuneGrid=gbmGrid,
metric=metricToMinimise,
bag.fraction=0.75) ## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 275278389189.7609 nan 0.0010 186958987.5845
## 2 275096851932.0083 nan 0.0010 187907940.7682
## 3 274911503269.5191 nan 0.0010 191168518.7768
## 4 274718934859.3489 nan 0.0010 164338935.8388
## 5 274535643343.0552 nan 0.0010 181269979.6445
## 6 274350185768.3365 nan 0.0010 172994518.0600
## 7 274170829210.1366 nan 0.0010 171819190.9260
## 8 273990785275.9526 nan 0.0010 211105699.6557
## 9 273813008754.8853 nan 0.0010 185301081.3369
## 10 273626472092.5972 nan 0.0010 170160312.7607
## 20 271827357910.1739 nan 0.0010 161819676.1451
## 40 268308880278.2411 nan 0.0010 149877042.8871
## 60 264937371284.4132 nan 0.0010 178582057.3807
## 80 261678010221.0354 nan 0.0010 150080298.7240
## 100 258526338408.5802 nan 0.0010 160464620.9745
## 120 255522891593.4722 nan 0.0010 154121375.8053
## 140 252604184076.0254 nan 0.0010 141460850.3660
## 160 249729904916.7012 nan 0.0010 133706679.0980
## 180 246974538594.9703 nan 0.0010 134849054.5480
## 200 244304695579.7412 nan 0.0010 115125297.1715
## 220 241700866774.8555 nan 0.0010 129014731.5133
## 240 239171295204.0070 nan 0.0010 95347810.1479
## 260 236741268305.0546 nan 0.0010 115189345.1775
## 280 234375556752.4021 nan 0.0010 120569939.7197
## 300 232058008428.9919 nan 0.0010 117622532.8877
## 320 229840022814.5402 nan 0.0010 98804864.2605
## 340 227664554134.1673 nan 0.0010 92735867.6532
## 360 225556704385.6057 nan 0.0010 88999398.3863
## 380 223505657514.9502 nan 0.0010 82262225.1874
## 400 221499352697.7135 nan 0.0010 69405321.8445
## 420 219591408494.5077 nan 0.0010 97948849.0043
## 440 217712322036.3884 nan 0.0010 95646773.3867
## 460 215861708555.0157 nan 0.0010 79882669.2735
## 480 214083263611.8399 nan 0.0010 84351147.9704
## 500 212352702441.9046 nan 0.0010 91084021.0043
## 520 210688640065.3882 nan 0.0010 69768058.8764
## 540 209049106360.3239 nan 0.0010 82197350.5871
## 560 207463800021.4343 nan 0.0010 72345586.0853
## 580 205935588666.5696 nan 0.0010 71424253.1169
## 600 204431229654.9357 nan 0.0010 73868673.6658
## 620 203001178614.5789 nan 0.0010 75949650.9809
## 640 201579342726.3109 nan 0.0010 68881154.0512
## 660 200177190156.0136 nan 0.0010 52844983.7593
## 680 198823968765.0274 nan 0.0010 47073934.7893
## 700 197510887959.3508 nan 0.0010 44255850.3739
## 720 196215474683.1043 nan 0.0010 61371299.0258
## 740 194968280105.2673 nan 0.0010 66277315.5398
## 760 193751440562.9292 nan 0.0010 60503303.8565
## 780 192558342128.4714 nan 0.0010 49508785.2812
## 800 191386312429.4855 nan 0.0010 43401259.0845
## 820 190241295547.2896 nan 0.0010 30654590.2315
## 840 189116591286.1570 nan 0.0010 52935146.2435
## 860 188018361740.9301 nan 0.0010 46005903.0360
## 880 186940129309.5481 nan 0.0010 54228729.8674
## 900 185896404146.4440 nan 0.0010 27259959.2795
## 920 184860088800.0395 nan 0.0010 27558121.3180
## 940 183848761869.4711 nan 0.0010 47928469.8147
## 960 182862742039.5021 nan 0.0010 42862275.0877
## 980 181897075980.1297 nan 0.0010 48647227.9197
## 1000 180942723901.3311 nan 0.0010 49225217.8887
## 1020 179986006862.5753 nan 0.0010 30509531.1299
## 1040 179054126259.0987 nan 0.0010 45851471.0465
## 1060 178143451033.3544 nan 0.0010 33530694.3210
## 1080 177239231644.4682 nan 0.0010 44062124.2472
## 1100 176338268870.1428 nan 0.0010 47125012.7860
## 1120 175469972622.8476 nan 0.0010 39089525.8702
## 1140 174602630972.2686 nan 0.0010 44807330.6595
## 1160 173757824547.0815 nan 0.0010 12180370.4402
## 1180 172928331196.7879 nan 0.0010 30402592.9605
## 1200 172108753295.7612 nan 0.0010 29549119.0441
## 1220 171305628755.7089 nan 0.0010 38015211.7293
## 1240 170511998800.7003 nan 0.0010 39196975.4601
## 1260 169715909899.1711 nan 0.0010 32528331.0849
## 1280 168927416312.0771 nan 0.0010 41080333.3048
## 1300 168167795989.6256 nan 0.0010 34420110.5168
## 1320 167410072807.0137 nan 0.0010 39909049.3907
## 1340 166663465305.3265 nan 0.0010 32454222.5717
## 1360 165909956135.2496 nan 0.0010 23583004.3303
## 1380 165171786197.3378 nan 0.0010 14248936.1637
## 1400 164442277844.7023 nan 0.0010 36988069.2459
## 1420 163721270975.5334 nan 0.0010 29748057.2511
## 1440 162999014791.9425 nan 0.0010 20834799.7432
## 1460 162305041487.9702 nan 0.0010 35784426.6032
## 1480 161615755246.8222 nan 0.0010 28967243.8919
## 1500 160938331654.2725 nan 0.0010 28216918.1149
## 1520 160254900060.1373 nan 0.0010 23361671.3121
## 1540 159593637331.8330 nan 0.0010 28077173.1525
## 1560 158935268052.8100 nan 0.0010 21513366.7326
## 1580 158285686162.0274 nan 0.0010 -1420250.1067
## 1600 157640205100.6161 nan 0.0010 33017699.8055
## 1620 157003173025.7951 nan 0.0010 29117345.9484
## 1640 156375207733.6259 nan 0.0010 17852800.9163
## 1660 155745179049.8995 nan 0.0010 26531714.8258
## 1680 155121763059.1350 nan 0.0010 23003391.1577
## 1700 154519470416.1617 nan 0.0010 29550598.3532
## 1720 153910982905.2832 nan 0.0010 18928620.0911
## 1740 153318776828.6030 nan 0.0010 30676045.4476
## 1760 152724815553.8795 nan 0.0010 28032637.1667
## 1780 152141197288.1154 nan 0.0010 14041831.7492
## 1800 151558216955.2797 nan 0.0010 15903548.2075
## 1820 150986972269.0981 nan 0.0010 23050664.2079
## 1840 150434220576.2066 nan 0.0010 27793681.8924
## 1860 149874287757.5957 nan 0.0010 14584227.2584
## 1880 149324060532.1367 nan 0.0010 19631519.1100
## 1900 148784214176.5950 nan 0.0010 21684381.4503
## 1920 148251174725.7135 nan 0.0010 23448046.9099
## 1940 147718529127.6306 nan 0.0010 29276937.8889
## 1960 147208599750.7157 nan 0.0010 23212475.9443
## 1980 146686757496.7602 nan 0.0010 26560990.9330
## 2000 146177932201.8746 nan 0.0010 8686412.5944
## 2020 145665975968.1343 nan 0.0010 25105702.6207
## 2040 145161215849.5309 nan 0.0010 22273211.0125
## 2060 144661801446.2237 nan 0.0010 26434143.9982
## 2080 144172254645.4548 nan 0.0010 24159792.4516
## 2100 143680160607.1190 nan 0.0010 25319802.7476
## 2120 143190154581.8694 nan 0.0010 17055583.9598
## 2140 142707381981.4225 nan 0.0010 12527416.1470
## 2160 142231567349.8415 nan 0.0010 23138065.8763
## 2180 141756439785.3144 nan 0.0010 22678591.0124
## 2200 141282660178.3693 nan 0.0010 14664933.8967
## 2220 140824329424.6932 nan 0.0010 2529278.9953
## 2240 140365027175.3090 nan 0.0010 13350514.8772
## 2260 139912195152.4867 nan 0.0010 21429678.8842
## 2280 139464651028.4916 nan 0.0010 20876581.9535
## 2300 139012208701.4876 nan 0.0010 19858321.5930
## 2320 138581810974.8875 nan 0.0010 17138927.5522
## 2340 138155625160.7159 nan 0.0010 18880411.9426
## 2360 137733003991.7748 nan 0.0010 15104008.4507
## 2380 137310516110.1309 nan 0.0010 17507652.2643
## 2400 136893066130.3839 nan 0.0010 20330068.4043
## 2420 136479565383.1948 nan 0.0010 16312551.5545
## 2440 136074114634.0565 nan 0.0010 15934357.6773
## 2460 135664907699.8038 nan 0.0010 21484370.5525
## 2480 135264273036.2541 nan 0.0010 18411592.3269
## 2500 134863919691.6277 nan 0.0010 19857310.8153
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 275155233544.8550 nan 0.0010 213116447.6800
## 2 274868170379.4314 nan 0.0010 320085691.7799
## 3 274596872520.6545 nan 0.0010 304275828.4575
## 4 274317833869.7914 nan 0.0010 314449580.3729
## 5 274014822753.8446 nan 0.0010 307025876.4690
## 6 273724177829.1596 nan 0.0010 218708757.7891
## 7 273437873216.9867 nan 0.0010 281098957.0750
## 8 273143657232.6679 nan 0.0010 251520603.0951
## 9 272866831397.3902 nan 0.0010 358961038.5025
## 10 272578186782.7641 nan 0.0010 211719207.9112
## 20 269712566877.7797 nan 0.0010 276135508.6134
## 40 264260014004.1794 nan 0.0010 353798011.6540
## 60 259042574374.3437 nan 0.0010 295522593.5875
## 80 253949215807.4811 nan 0.0010 226132657.1233
## 100 249084208201.2206 nan 0.0010 237999236.4369
## 120 244329473332.0612 nan 0.0010 183927642.6841
## 140 239808604890.4897 nan 0.0010 191673860.1483
## 160 235365741436.7652 nan 0.0010 225607401.8512
## 180 231112997727.8018 nan 0.0010 238422943.4999
## 200 226960613314.1595 nan 0.0010 184469092.4653
## 220 222929089936.4607 nan 0.0010 207111336.5923
## 240 219070873003.3553 nan 0.0010 191029447.9966
## 260 215282706740.0140 nan 0.0010 182063659.2810
## 280 211642265502.8831 nan 0.0010 193605933.8517
## 300 208078616619.9762 nan 0.0010 137437259.2537
## 320 204625596024.7585 nan 0.0010 114005582.5578
## 340 201311875655.3134 nan 0.0010 123344578.4885
## 360 198064515620.0251 nan 0.0010 160206304.6736
## 380 194900519550.0978 nan 0.0010 150826987.9933
## 400 191847967494.4754 nan 0.0010 143646473.9031
## 420 188870319535.7358 nan 0.0010 111406504.0998
## 440 185983173448.8842 nan 0.0010 121271003.9701
## 460 183234236491.6755 nan 0.0010 100885403.6338
## 480 180503994244.6477 nan 0.0010 124435057.6097
## 500 177895352922.6484 nan 0.0010 109708725.3846
## 520 175348646236.6152 nan 0.0010 89000712.6964
## 540 172857639548.1531 nan 0.0010 101247183.6423
## 560 170434219769.3228 nan 0.0010 103267335.0805
## 580 168122118047.9714 nan 0.0010 104543599.9711
## 600 165843219693.3160 nan 0.0010 109719103.5187
## 620 163632395085.0066 nan 0.0010 96700313.2347
## 640 161467552156.1600 nan 0.0010 83497850.6839
## 660 159368186024.3430 nan 0.0010 99232498.4262
## 680 157341319703.5193 nan 0.0010 73980731.3424
## 700 155324901011.5516 nan 0.0010 86025678.1131
## 720 153421293452.4287 nan 0.0010 65696664.2174
## 740 151543464875.1176 nan 0.0010 79212607.2737
## 760 149691046941.4599 nan 0.0010 75276752.4478
## 780 147934935566.1309 nan 0.0010 49340422.5572
## 800 146226075757.9880 nan 0.0010 89051281.4059
## 820 144484863017.9479 nan 0.0010 99865010.7988
## 840 142807776916.1649 nan 0.0010 59753408.8604
## 860 141190538622.6388 nan 0.0010 88060286.9656
## 880 139605090885.8456 nan 0.0010 58667352.6933
## 900 138044255140.9820 nan 0.0010 67358958.8222
## 920 136545449850.4771 nan 0.0010 70087071.6627
## 940 135073576139.7704 nan 0.0010 37992052.3677
## 960 133631466599.7324 nan 0.0010 53515734.1475
## 980 132189422430.2681 nan 0.0010 48705450.7373
## 1000 130796184534.9594 nan 0.0010 58161970.5358
## 1020 129440170427.9184 nan 0.0010 59206110.9571
## 1040 128150016754.5781 nan 0.0010 68580855.5803
## 1060 126841915667.7406 nan 0.0010 61478037.9715
## 1080 125574236866.3755 nan 0.0010 45010527.8086
## 1100 124334130906.1096 nan 0.0010 63749233.3688
## 1120 123141320413.1392 nan 0.0010 40284987.9827
## 1140 121953258933.1394 nan 0.0010 58885164.0857
## 1160 120801879808.7124 nan 0.0010 77679117.1997
## 1180 119657307386.3570 nan 0.0010 71119339.3244
## 1200 118565177269.5439 nan 0.0010 32437372.6924
## 1220 117481648171.4363 nan 0.0010 38544790.8735
## 1240 116410296180.9745 nan 0.0010 46761936.8792
## 1260 115354687458.7558 nan 0.0010 28251607.1094
## 1280 114309319002.2692 nan 0.0010 47653229.7561
## 1300 113283068133.5718 nan 0.0010 55566903.7556
## 1320 112315415618.5916 nan 0.0010 44979863.3160
## 1340 111328738767.2209 nan 0.0010 22043925.3644
## 1360 110355734691.9685 nan 0.0010 44696721.8286
## 1380 109409124356.5306 nan 0.0010 46952950.0777
## 1400 108481068948.9866 nan 0.0010 87608827.4297
## 1420 107568109473.4810 nan 0.0010 45803704.7224
## 1440 106686673400.7432 nan 0.0010 47969017.3624
## 1460 105812162071.4566 nan 0.0010 23238011.7754
## 1480 104947033369.6737 nan 0.0010 45394966.3609
## 1500 104082154535.3644 nan 0.0010 28387703.2347
## 1520 103227534341.1911 nan 0.0010 27789201.5198
## 1540 102405145471.3346 nan 0.0010 15929530.7550
## 1560 101579301528.2006 nan 0.0010 45553264.5683
## 1580 100768878323.3701 nan 0.0010 48722090.6449
## 1600 99968047343.8874 nan 0.0010 39267061.8065
## 1620 99186714555.3442 nan 0.0010 24556461.3009
## 1640 98374550081.6803 nan 0.0010 40478559.3506
## 1660 97615681966.1272 nan 0.0010 34843532.2020
## 1680 96846184592.0837 nan 0.0010 49767978.0896
## 1700 96118492331.4173 nan 0.0010 33878826.6270
## 1720 95418243590.8176 nan 0.0010 17204976.2568
## 1740 94693702453.4755 nan 0.0010 33505245.3107
## 1760 94012147056.8281 nan 0.0010 35797127.3447
## 1780 93299060389.5283 nan 0.0010 28253766.8689
## 1800 92633340174.9358 nan 0.0010 22028356.9719
## 1820 91934300056.0557 nan 0.0010 29066980.6022
## 1840 91252337003.3535 nan 0.0010 26992184.3974
## 1860 90575000430.1675 nan 0.0010 16943939.7649
## 1880 89936762526.3299 nan 0.0010 25578959.6626
## 1900 89298516328.4757 nan 0.0010 20618824.0415
## 1920 88676902337.6743 nan 0.0010 34520016.5099
## 1940 88074725112.4953 nan 0.0010 28586042.3860
## 1960 87449882194.7308 nan 0.0010 31107390.4501
## 1980 86838256834.9145 nan 0.0010 26035001.9886
## 2000 86231402619.6751 nan 0.0010 13139121.9997
## 2020 85647937119.5902 nan 0.0010 13151578.1509
## 2040 85078340908.6170 nan 0.0010 24457554.2969
## 2060 84493795334.5237 nan 0.0010 34753847.9980
## 2080 83920035829.4594 nan 0.0010 19478018.7497
## 2100 83350498589.9837 nan 0.0010 10950623.8578
## 2120 82802152181.5322 nan 0.0010 27671015.0270
## 2140 82279111632.1708 nan 0.0010 13119500.4654
## 2160 81724558529.2366 nan 0.0010 13142114.1430
## 2180 81212689014.1063 nan 0.0010 23406094.9159
## 2200 80706427114.2766 nan 0.0010 20960261.9769
## 2220 80204038585.6108 nan 0.0010 28068236.5554
## 2240 79721753440.7257 nan 0.0010 -721669.6247
## 2260 79241668732.7311 nan 0.0010 18123499.4667
## 2280 78747660257.2383 nan 0.0010 15277979.3132
## 2300 78270075245.3741 nan 0.0010 12136726.7709
## 2320 77777063848.5836 nan 0.0010 30745573.7035
## 2340 77305429498.7150 nan 0.0010 20597440.4594
## 2360 76842391319.5946 nan 0.0010 18032098.5384
## 2380 76380831319.1370 nan 0.0010 6227061.8710
## 2400 75957534440.2994 nan 0.0010 9798417.8610
## 2420 75532356569.2490 nan 0.0010 24393193.9219
## 2440 75104326909.5211 nan 0.0010 25532577.8799
## 2460 74686924392.3395 nan 0.0010 10798798.0915
## 2480 74258434277.3655 nan 0.0010 19389170.0049
## 2500 73840169616.2012 nan 0.0010 13955104.7339
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 275125181221.6075 nan 0.0010 306717434.8725
## 2 274792627709.7831 nan 0.0010 368635417.1390
## 3 274455022306.3159 nan 0.0010 307242222.6276
## 4 274123619940.9093 nan 0.0010 287439810.3326
## 5 273781418815.2455 nan 0.0010 334430501.1783
## 6 273468993382.0545 nan 0.0010 339096041.6289
## 7 273133055286.6245 nan 0.0010 269674131.5094
## 8 272791803570.8103 nan 0.0010 253838479.1780
## 9 272458778133.8328 nan 0.0010 331453779.9229
## 10 272136147238.2788 nan 0.0010 262265891.5228
## 20 268942883699.6267 nan 0.0010 316065302.8213
## 40 262671009975.3833 nan 0.0010 314708722.4035
## 60 256695554255.9662 nan 0.0010 268667225.0010
## 80 250870354045.3753 nan 0.0010 221540218.3306
## 100 245268978872.6091 nan 0.0010 265921169.7269
## 120 239896738997.3258 nan 0.0010 267849071.8050
## 140 234671461508.7578 nan 0.0010 267881573.8068
## 160 229611657183.6588 nan 0.0010 199413324.7215
## 180 224724919033.5171 nan 0.0010 263904329.3659
## 200 219982404988.7466 nan 0.0010 174862287.6008
## 220 215391015196.6473 nan 0.0010 218888461.5069
## 240 210980632065.6746 nan 0.0010 232103903.2329
## 260 206685485596.4787 nan 0.0010 162451008.4965
## 280 202570272385.7181 nan 0.0010 219144295.7754
## 300 198525160194.5521 nan 0.0010 195909862.1561
## 320 194647840670.9676 nan 0.0010 133228077.3334
## 340 190864362458.3839 nan 0.0010 196389675.8594
## 360 187210030531.2715 nan 0.0010 151086817.8788
## 380 183716495306.9412 nan 0.0010 138469674.6963
## 400 180288087685.7441 nan 0.0010 141239496.8706
## 420 176978744352.9390 nan 0.0010 144676331.4405
## 440 173749389257.2359 nan 0.0010 133747690.8555
## 460 170613303378.8399 nan 0.0010 137384937.4488
## 480 167541808976.0872 nan 0.0010 141603861.2047
## 500 164621350924.5423 nan 0.0010 134183607.9205
## 520 161780575094.7440 nan 0.0010 122501280.1997
## 540 159036472978.5881 nan 0.0010 125221072.0765
## 560 156373341996.2281 nan 0.0010 117323239.7605
## 580 153777905872.2397 nan 0.0010 113802796.3028
## 600 151231747835.9716 nan 0.0010 125682450.8569
## 620 148798412387.6873 nan 0.0010 108028833.2547
## 640 146423620536.1582 nan 0.0010 90220347.3691
## 660 144054653310.3124 nan 0.0010 71734585.0338
## 680 141759266019.3258 nan 0.0010 119997375.2570
## 700 139564480256.4451 nan 0.0010 133331840.8006
## 720 137429926730.9115 nan 0.0010 97533121.7288
## 740 135401417314.1897 nan 0.0010 109025303.6910
## 760 133354905258.0142 nan 0.0010 108265047.7802
## 780 131432188569.7619 nan 0.0010 84584039.3138
## 800 129519583110.2908 nan 0.0010 96666956.1847
## 820 127678552090.5610 nan 0.0010 90221363.3949
## 840 125894406745.5992 nan 0.0010 81399524.7171
## 860 124147254037.1505 nan 0.0010 68092185.6757
## 880 122440307099.7066 nan 0.0010 68283952.6334
## 900 120765063709.1290 nan 0.0010 40010684.1040
## 920 119138220634.6151 nan 0.0010 61130062.5165
## 940 117549106387.4158 nan 0.0010 51443496.3952
## 960 115988421246.7103 nan 0.0010 97968417.8289
## 980 114481584719.0707 nan 0.0010 65032047.0917
## 1000 113012475053.2651 nan 0.0010 55600275.5430
## 1020 111550610255.6074 nan 0.0010 52527404.1839
## 1040 110145259239.5487 nan 0.0010 54536888.5596
## 1060 108776073129.2598 nan 0.0010 55078358.1179
## 1080 107432216876.3723 nan 0.0010 53549607.1920
## 1100 106115069404.7959 nan 0.0010 60137763.5716
## 1120 104845967749.5045 nan 0.0010 75830409.7283
## 1140 103598707901.7601 nan 0.0010 67746384.8040
## 1160 102372239798.2352 nan 0.0010 47271774.9573
## 1180 101193074922.1543 nan 0.0010 51529561.0733
## 1200 100048040040.6197 nan 0.0010 39876728.2702
## 1220 98901431059.9101 nan 0.0010 42777510.6358
## 1240 97805024200.2866 nan 0.0010 44089100.9019
## 1260 96710269642.6167 nan 0.0010 53022817.7468
## 1280 95633038711.7429 nan 0.0010 44899366.5071
## 1300 94598801760.6216 nan 0.0010 42229882.5581
## 1320 93578937675.3960 nan 0.0010 49716465.8486
## 1340 92582109631.4328 nan 0.0010 29456813.9056
## 1360 91593451913.2915 nan 0.0010 27570803.4621
## 1380 90666194515.7055 nan 0.0010 40091587.5322
## 1400 89738610774.3320 nan 0.0010 37847774.4017
## 1420 88827510520.7775 nan 0.0010 41822669.7750
## 1440 87935120919.2330 nan 0.0010 37275074.8726
## 1460 87060724518.9910 nan 0.0010 39841661.5295
## 1480 86207491777.9967 nan 0.0010 42724424.1206
## 1500 85378902960.6325 nan 0.0010 23494726.7271
## 1520 84561778728.2926 nan 0.0010 38341047.5930
## 1540 83768432282.1018 nan 0.0010 34374756.1166
## 1560 82967479998.9926 nan 0.0010 31805827.0750
## 1580 82217007187.5235 nan 0.0010 34532410.9370
## 1600 81470859224.0279 nan 0.0010 24149829.8052
## 1620 80747120323.5704 nan 0.0010 37724998.7472
## 1640 80008638612.2110 nan 0.0010 26598312.1101
## 1660 79302394535.1602 nan 0.0010 19918082.8239
## 1680 78581874916.3012 nan 0.0010 26155379.5201
## 1700 77886064737.1629 nan 0.0010 19075886.0425
## 1720 77236614336.9823 nan 0.0010 35419890.2277
## 1740 76572686695.7747 nan 0.0010 32527358.6488
## 1760 75928576057.7390 nan 0.0010 24336947.8712
## 1780 75293945004.7240 nan 0.0010 29059997.5153
## 1800 74687916127.3586 nan 0.0010 25808245.9391
## 1820 74075463474.1145 nan 0.0010 21447449.5984
## 1840 73483390708.0222 nan 0.0010 21053022.2108
## 1860 72901444622.1404 nan 0.0010 27897128.8413
## 1880 72346072891.8819 nan 0.0010 24137901.1664
## 1900 71786095679.1011 nan 0.0010 21660515.5638
## 1920 71223909864.9180 nan 0.0010 22844281.6087
## 1940 70651219200.3406 nan 0.0010 33931658.7474
## 1960 70111581724.7264 nan 0.0010 24312803.3452
## 1980 69599668340.2997 nan 0.0010 24095027.7318
## 2000 69061673673.0897 nan 0.0010 16658707.5107
## 2020 68548913240.4294 nan 0.0010 19847988.0501
## 2040 68053301498.7312 nan 0.0010 15630147.9056
## 2060 67562634408.6119 nan 0.0010 23834986.0896
## 2080 67078391872.2721 nan 0.0010 11779819.4150
## 2100 66593882289.0790 nan 0.0010 8304251.9940
## 2120 66127465517.1926 nan 0.0010 18962520.5149
## 2140 65663082218.4932 nan 0.0010 32750896.2993
## 2160 65215007950.3431 nan 0.0010 17082415.9228
## 2180 64780153037.3429 nan 0.0010 5997865.6632
## 2200 64347195916.6017 nan 0.0010 12634313.9600
## 2220 63925216508.8812 nan 0.0010 18844959.4396
## 2240 63513656721.7785 nan 0.0010 12963640.2355
## 2260 63100319805.1851 nan 0.0010 13355486.9427
## 2280 62685818438.5609 nan 0.0010 8311332.2064
## 2300 62282586350.8236 nan 0.0010 12252635.1041
## 2320 61889859645.9870 nan 0.0010 20850582.9464
## 2340 61516655023.4986 nan 0.0010 13744031.0374
## 2360 61148489236.0149 nan 0.0010 13748779.8036
## 2380 60799267710.9449 nan 0.0010 14642530.0374
## 2400 60436682391.3397 nan 0.0010 28183066.3682
## 2420 60089234774.6412 nan 0.0010 7260863.5977
## 2440 59744652939.8077 nan 0.0010 8493332.6174
## 2460 59400353527.0363 nan 0.0010 23009152.1468
## 2480 59061740168.9920 nan 0.0010 8346593.8462
## 2500 58731658979.1424 nan 0.0010 13153045.2205
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 273734560704.5083 nan 0.0100 1897942726.4217
## 2 271809706332.7357 nan 0.0100 1659767389.9206
## 3 270049841233.0580 nan 0.0100 1797920547.9226
## 4 268282487122.5491 nan 0.0100 1576311250.2383
## 5 266570257501.0912 nan 0.0100 1660654198.6573
## 6 264956054161.4348 nan 0.0100 1938250219.0741
## 7 263297152815.4327 nan 0.0100 1375972155.2304
## 8 261732105193.3354 nan 0.0100 1404883606.7814
## 9 260139933539.6293 nan 0.0100 1583728379.9776
## 10 258577228761.7943 nan 0.0100 1743926653.1565
## 20 244544770108.6364 nan 0.0100 1374462939.9007
## 40 221658421220.4990 nan 0.0100 963650276.6592
## 60 204563959679.6907 nan 0.0100 782761731.3459
## 80 191633893213.9770 nan 0.0100 542150189.8322
## 100 181046398822.0826 nan 0.0100 451555469.0433
## 120 172161967625.7983 nan 0.0100 394359555.7829
## 140 164431415612.2774 nan 0.0100 252920277.8251
## 160 157706331786.5692 nan 0.0100 303422410.0057
## 180 151619305427.8673 nan 0.0100 288748036.6345
## 200 146275185967.2461 nan 0.0100 211466772.5440
## 220 141244823178.4547 nan 0.0100 213443092.7302
## 240 136808687888.2426 nan 0.0100 202228307.9604
## 260 132811573079.3952 nan 0.0100 94315016.0426
## 280 129247069486.1062 nan 0.0100 114933198.8666
## 300 125944178747.1600 nan 0.0100 144374286.0534
## 320 122897196937.6628 nan 0.0100 139217269.5206
## 340 120195916863.9382 nan 0.0100 -24222652.6869
## 360 117637084998.9129 nan 0.0100 42560630.5388
## 380 115200423962.3192 nan 0.0100 66244756.3276
## 400 113039841926.1210 nan 0.0100 111354324.7469
## 420 110999093348.9151 nan 0.0100 100011121.8462
## 440 109033559257.0691 nan 0.0100 93789018.3120
## 460 107291989921.7293 nan 0.0100 84949880.7057
## 480 105659762087.0080 nan 0.0100 10320244.7571
## 500 104117486885.3667 nan 0.0100 24622391.6053
## 520 102678505562.9384 nan 0.0100 66030194.0167
## 540 101307288273.4100 nan 0.0100 68436795.8934
## 560 100040294960.2811 nan 0.0100 64457373.1303
## 580 98852505004.0526 nan 0.0100 26267665.8179
## 600 97743146392.1123 nan 0.0100 15099702.2397
## 620 96670639186.1700 nan 0.0100 28913984.4499
## 640 95686197393.6128 nan 0.0100 8314012.1427
## 660 94772172750.1351 nan 0.0100 2637827.9282
## 680 93924641845.0860 nan 0.0100 -46614311.0087
## 700 93131174695.2449 nan 0.0100 3858172.1847
## 720 92395181199.1657 nan 0.0100 36616624.9854
## 740 91707136753.7156 nan 0.0100 5092157.5944
## 760 91028222755.8563 nan 0.0100 24748756.3851
## 780 90374442296.8304 nan 0.0100 10310196.5192
## 800 89788313794.6014 nan 0.0100 -9610769.9542
## 820 89267027397.8952 nan 0.0100 24282718.2839
## 840 88745479400.9579 nan 0.0100 22021761.0524
## 860 88232060782.6250 nan 0.0100 22736678.1059
## 880 87779370803.3976 nan 0.0100 19568138.0682
## 900 87348510485.9802 nan 0.0100 12695746.6525
## 920 86935055614.5423 nan 0.0100 19009031.5405
## 940 86538557934.8631 nan 0.0100 852944.0673
## 960 86174137164.8389 nan 0.0100 17487655.3852
## 980 85840904884.3471 nan 0.0100 -23119580.5067
## 1000 85518350216.7070 nan 0.0100 1200944.9272
## 1020 85200130516.2387 nan 0.0100 13668383.5942
## 1040 84889070080.6626 nan 0.0100 8957843.9226
## 1060 84584269031.9715 nan 0.0100 9836311.6729
## 1080 84314904846.8146 nan 0.0100 10233020.1658
## 1100 84090719246.0101 nan 0.0100 -72094143.3825
## 1120 83852333394.6739 nan 0.0100 1846017.3876
## 1140 83615486092.3862 nan 0.0100 3511716.3529
## 1160 83406414550.9365 nan 0.0100 7958605.8630
## 1180 83190538138.9754 nan 0.0100 10073561.5129
## 1200 82997009256.2820 nan 0.0100 6733890.9303
## 1220 82811181979.3283 nan 0.0100 6031809.0217
## 1240 82628333272.3936 nan 0.0100 6380722.6596
## 1260 82456282882.6647 nan 0.0100 -34426832.5853
## 1280 82286842522.8634 nan 0.0100 -9251802.9991
## 1300 82123224730.1980 nan 0.0100 9880952.8829
## 1320 81948913405.6610 nan 0.0100 6154626.2921
## 1340 81780194184.2625 nan 0.0100 1877852.1540
## 1360 81635127481.2891 nan 0.0100 2167170.3021
## 1380 81494881062.1435 nan 0.0100 5773699.0570
## 1400 81360965323.3791 nan 0.0100 -8845830.5893
## 1420 81223823511.1087 nan 0.0100 -34319366.6951
## 1440 81108644980.6513 nan 0.0100 5452805.1540
## 1460 81001842739.2894 nan 0.0100 3532090.3497
## 1480 80887505827.8039 nan 0.0100 -10104177.6746
## 1500 80752419272.7881 nan 0.0100 293492.9654
## 1520 80643808626.8318 nan 0.0100 -19303509.0370
## 1540 80531760750.8736 nan 0.0100 -5096613.1881
## 1560 80418516767.1815 nan 0.0100 2441954.7809
## 1580 80340140191.9269 nan 0.0100 -6697621.8972
## 1600 80258890009.6015 nan 0.0100 -4586379.0033
## 1620 80149358310.5899 nan 0.0100 1880791.0935
## 1640 80044151292.7091 nan 0.0100 -12265805.6990
## 1660 79955913327.8381 nan 0.0100 -19423281.7565
## 1680 79874417144.6587 nan 0.0100 -39242093.7611
## 1700 79780169575.7856 nan 0.0100 2551864.9846
## 1720 79695865912.5164 nan 0.0100 -12775081.0515
## 1740 79611305212.3455 nan 0.0100 -6142114.2789
## 1760 79515249465.8795 nan 0.0100 3221180.6583
## 1780 79446607479.9852 nan 0.0100 -31974392.0928
## 1800 79367446135.1563 nan 0.0100 994811.6778
## 1820 79290571186.2733 nan 0.0100 -448873.2639
## 1840 79221558862.8549 nan 0.0100 -52604944.6556
## 1860 79140261730.3512 nan 0.0100 3701739.2911
## 1880 79068442977.7162 nan 0.0100 -7183776.8623
## 1900 78999809277.2486 nan 0.0100 4496827.1743
## 1920 78931852052.4850 nan 0.0100 -39872762.5335
## 1940 78867375852.8128 nan 0.0100 2788314.4343
## 1960 78805199423.7712 nan 0.0100 3085293.2486
## 1980 78749780966.6307 nan 0.0100 -19264199.4928
## 2000 78696188730.7076 nan 0.0100 2001750.9316
## 2020 78626725878.3617 nan 0.0100 4035367.8757
## 2040 78565305621.5580 nan 0.0100 -15292537.0940
## 2060 78507378880.9770 nan 0.0100 -19411745.0044
## 2080 78449002196.6339 nan 0.0100 -8420123.6290
## 2100 78386313129.0082 nan 0.0100 -16477914.8730
## 2120 78329822138.6795 nan 0.0100 -10660955.0851
## 2140 78275155960.4957 nan 0.0100 506857.6110
## 2160 78218995320.3497 nan 0.0100 -31053952.2675
## 2180 78171800232.0548 nan 0.0100 -44605242.1477
## 2200 78121898590.5478 nan 0.0100 -5564326.3893
## 2220 78069096112.7561 nan 0.0100 -17275722.9840
## 2240 78009450562.4189 nan 0.0100 -35880030.6424
## 2260 77948310717.9634 nan 0.0100 1548275.3069
## 2280 77895394349.3676 nan 0.0100 -5408133.6304
## 2300 77840983350.5126 nan 0.0100 -13110318.6580
## 2320 77779771255.5914 nan 0.0100 -14571194.9429
## 2340 77718649391.5565 nan 0.0100 1311755.1185
## 2360 77668072179.4760 nan 0.0100 -14384870.3150
## 2380 77621880081.4441 nan 0.0100 -13800241.8001
## 2400 77574502167.8555 nan 0.0100 -309715.6509
## 2420 77524133458.5893 nan 0.0100 -17464612.6199
## 2440 77470633360.0948 nan 0.0100 2059947.9838
## 2460 77423313579.7564 nan 0.0100 -13616463.0264
## 2480 77363585099.2811 nan 0.0100 -4355602.5851
## 2500 77316649119.9108 nan 0.0100 -13613147.6408
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 272788020080.1528 nan 0.0100 2835928479.8154
## 2 269857339137.4583 nan 0.0100 3348442824.6794
## 3 267060258716.1715 nan 0.0100 2894467250.8329
## 4 264356321472.0211 nan 0.0100 2897694741.7048
## 5 261452813401.2619 nan 0.0100 2527282930.4667
## 6 258814885339.6733 nan 0.0100 2420428022.3588
## 7 256209606391.8248 nan 0.0100 2337600257.4546
## 8 253758244230.9784 nan 0.0100 2979026681.6453
## 9 251136683962.0675 nan 0.0100 3094068509.3744
## 10 248791768396.1685 nan 0.0100 2526339133.0533
## 20 226549760342.0745 nan 0.0100 1332315353.3310
## 40 191656164758.3137 nan 0.0100 1461451010.4767
## 60 165685235584.9471 nan 0.0100 1421800308.9466
## 80 146001248150.5209 nan 0.0100 842299435.3291
## 100 130795291433.8551 nan 0.0100 471728717.2880
## 120 118299085548.7034 nan 0.0100 479977316.6854
## 140 108053209002.2962 nan 0.0100 441636283.5541
## 160 99396171132.5969 nan 0.0100 258750270.2945
## 180 92060595482.8422 nan 0.0100 529151155.1834
## 200 85819057829.7308 nan 0.0100 179480850.2937
## 220 80405201048.1507 nan 0.0100 124230648.1097
## 240 75779784289.8770 nan 0.0100 122161671.0100
## 260 71651850600.2115 nan 0.0100 261339152.3153
## 280 68143374059.1861 nan 0.0100 193900982.1124
## 300 65129497091.3080 nan 0.0100 76337729.5962
## 320 62441999220.0219 nan 0.0100 148258817.8965
## 340 60175949786.3513 nan 0.0100 9278989.5614
## 360 58184499907.5795 nan 0.0100 69728005.0910
## 380 56459759661.6801 nan 0.0100 7988224.8469
## 400 54948908026.6471 nan 0.0100 26740686.1228
## 420 53625273189.5202 nan 0.0100 68831450.8715
## 440 52435315684.9432 nan 0.0100 59616803.6556
## 460 51341410293.0745 nan 0.0100 21357347.1623
## 480 50378071672.3800 nan 0.0100 41757564.1307
## 500 49576267827.3827 nan 0.0100 43522224.6826
## 520 48837600173.1816 nan 0.0100 26275376.3517
## 540 48192956041.0376 nan 0.0100 6464910.4154
## 560 47588896286.6076 nan 0.0100 19925716.7553
## 580 47042470654.5404 nan 0.0100 8253164.8168
## 600 46510999728.0777 nan 0.0100 18960612.7078
## 620 46035089456.3659 nan 0.0100 -18525820.9818
## 640 45576325305.3186 nan 0.0100 -11377323.3549
## 660 45166872836.5102 nan 0.0100 9359875.1735
## 680 44774741886.1770 nan 0.0100 8267410.0612
## 700 44397422132.4839 nan 0.0100 13907584.2545
## 720 44061910355.6947 nan 0.0100 -34883585.9355
## 740 43722384209.2180 nan 0.0100 -8079014.5702
## 760 43411232791.9095 nan 0.0100 -10363268.6441
## 780 43111093465.9113 nan 0.0100 9182434.9281
## 800 42828041959.2161 nan 0.0100 2054083.2828
## 820 42573338628.8492 nan 0.0100 -9494382.6331
## 840 42278305067.0803 nan 0.0100 5576485.4415
## 860 42026140896.7982 nan 0.0100 -16140996.6507
## 880 41742864978.6239 nan 0.0100 -1890231.0856
## 900 41480025399.1225 nan 0.0100 -32779628.5402
## 920 41203744163.7245 nan 0.0100 -3496165.6178
## 940 40921609409.8133 nan 0.0100 -10345206.1736
## 960 40677839480.9837 nan 0.0100 6987167.3421
## 980 40450621482.0972 nan 0.0100 2776987.9476
## 1000 40214209446.5319 nan 0.0100 3703197.2410
## 1020 39988216659.2191 nan 0.0100 -3819484.6209
## 1040 39743536557.3470 nan 0.0100 -21716984.0465
## 1060 39537007367.1023 nan 0.0100 310779.0435
## 1080 39332656273.0895 nan 0.0100 -5452647.4344
## 1100 39128875691.5562 nan 0.0100 -15930533.0976
## 1120 38900359708.8110 nan 0.0100 -32776869.0509
## 1140 38712641379.3057 nan 0.0100 3097142.4749
## 1160 38503189559.8094 nan 0.0100 -23369685.2418
## 1180 38341001177.4918 nan 0.0100 -4434374.0674
## 1200 38148165246.6200 nan 0.0100 -8195506.2583
## 1220 37965216560.9086 nan 0.0100 -15561593.7339
## 1240 37803027926.9758 nan 0.0100 -31163420.8364
## 1260 37598267583.3989 nan 0.0100 -9894911.7114
## 1280 37416932572.6339 nan 0.0100 -17829436.0450
## 1300 37246816747.5938 nan 0.0100 4162170.4150
## 1320 37070884508.4320 nan 0.0100 3355200.1671
## 1340 36906571217.6499 nan 0.0100 -2976943.5951
## 1360 36701750060.8153 nan 0.0100 -977256.3702
## 1380 36570661297.0252 nan 0.0100 -2305369.0469
## 1400 36397232392.8203 nan 0.0100 -8419727.4228
## 1420 36241594707.7411 nan 0.0100 -3894770.1501
## 1440 36068968919.2364 nan 0.0100 -1857710.7641
## 1460 35920427828.9011 nan 0.0100 -30587114.8818
## 1480 35770086097.6117 nan 0.0100 -12210848.3257
## 1500 35648308792.7584 nan 0.0100 -2732070.9204
## 1520 35494591249.8936 nan 0.0100 -4978604.0602
## 1540 35378066752.2698 nan 0.0100 -5936529.1318
## 1560 35246097206.1775 nan 0.0100 -16739802.5451
## 1580 35105293824.2449 nan 0.0100 -16443481.8756
## 1600 34977881073.7721 nan 0.0100 -20158744.1019
## 1620 34821170218.5837 nan 0.0100 -3361779.9830
## 1640 34695370851.6474 nan 0.0100 -12665115.6631
## 1660 34564560211.8890 nan 0.0100 -2314721.3704
## 1680 34428604797.6836 nan 0.0100 252527.5975
## 1700 34303105868.4596 nan 0.0100 -14847565.5738
## 1720 34165195618.4557 nan 0.0100 2370457.9368
## 1740 34016007396.3048 nan 0.0100 -3924441.1675
## 1760 33859747531.0868 nan 0.0100 -5275898.6763
## 1780 33756667890.1377 nan 0.0100 -8115502.5730
## 1800 33656811907.5945 nan 0.0100 -9468476.1090
## 1820 33537455415.5568 nan 0.0100 -21680231.6777
## 1840 33429223815.5461 nan 0.0100 -6999974.9579
## 1860 33321891445.3811 nan 0.0100 -24930055.9611
## 1880 33204448189.9061 nan 0.0100 1775958.4937
## 1900 33094839175.7741 nan 0.0100 -9101277.2470
## 1920 32978911213.7326 nan 0.0100 -13821468.3807
## 1940 32852317436.5156 nan 0.0100 -1444627.2486
## 1960 32716299413.6879 nan 0.0100 -7247776.0686
## 1980 32598379068.0316 nan 0.0100 -484696.0329
## 2000 32500365555.4792 nan 0.0100 -53321821.4706
## 2020 32409975995.8706 nan 0.0100 -14898423.0430
## 2040 32322158119.7438 nan 0.0100 -11249074.2268
## 2060 32214176084.4313 nan 0.0100 -20753601.2863
## 2080 32091662151.4072 nan 0.0100 -6254927.2025
## 2100 31951071029.4791 nan 0.0100 -15872492.2416
## 2120 31846995930.8640 nan 0.0100 -8923458.5419
## 2140 31736925664.0011 nan 0.0100 -21023463.7750
## 2160 31626470192.2566 nan 0.0100 -3145050.6963
## 2180 31520108323.2013 nan 0.0100 -6672360.1380
## 2200 31433050981.8993 nan 0.0100 -3755478.1154
## 2220 31352998541.6425 nan 0.0100 -10872778.9624
## 2240 31244558607.5437 nan 0.0100 -5336746.0893
## 2260 31160764534.0457 nan 0.0100 1011441.3937
## 2280 31077739296.0179 nan 0.0100 -1350226.5929
## 2300 30955927978.6592 nan 0.0100 2032794.4224
## 2320 30874180244.6202 nan 0.0100 -1102127.7040
## 2340 30782231536.7165 nan 0.0100 -6360187.6477
## 2360 30667561801.4847 nan 0.0100 3268195.7340
## 2380 30566630767.6019 nan 0.0100 -2800459.3406
## 2400 30463757225.0639 nan 0.0100 -4707982.5239
## 2420 30381211895.8775 nan 0.0100 -6838757.4735
## 2440 30275387078.9820 nan 0.0100 -9467867.0581
## 2460 30178932529.0757 nan 0.0100 -5717391.8162
## 2480 30091927193.5443 nan 0.0100 -3694689.2727
## 2500 29999947461.6431 nan 0.0100 -11187431.9194
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 272142246748.7943 nan 0.0100 2794510096.0989
## 2 269007591127.7466 nan 0.0100 3043503768.4825
## 3 265934543949.9106 nan 0.0100 2716927172.3585
## 4 262958566444.2583 nan 0.0100 3004731639.3214
## 5 259947207043.9651 nan 0.0100 3093867207.1969
## 6 257069699536.0667 nan 0.0100 2935657532.7780
## 7 254058761846.5554 nan 0.0100 2089827121.8724
## 8 251134557488.1223 nan 0.0100 2539166787.2414
## 9 248273628383.0329 nan 0.0100 2485261013.5264
## 10 245534112584.7347 nan 0.0100 2688795877.4400
## 20 220232763878.5384 nan 0.0100 2425704167.2350
## 40 180603854059.2166 nan 0.0100 1151748909.8007
## 60 151681746045.8534 nan 0.0100 1075966342.9778
## 80 130159479954.8896 nan 0.0100 991270166.3356
## 100 113413697585.8971 nan 0.0100 798026122.6887
## 120 100559117474.2584 nan 0.0100 422132300.4279
## 140 90002541976.4484 nan 0.0100 365535620.8240
## 160 81985626001.1996 nan 0.0100 351101748.0046
## 180 75219046279.5033 nan 0.0100 207356911.4934
## 200 69546121162.1815 nan 0.0100 113535150.6899
## 220 64785378370.3032 nan 0.0100 115271094.7589
## 240 60742674171.9428 nan 0.0100 106553201.4154
## 260 57446626801.7458 nan 0.0100 143333616.7657
## 280 54735044862.3193 nan 0.0100 77017237.3405
## 300 52370374749.6674 nan 0.0100 59625268.2670
## 320 50335644752.8054 nan 0.0100 -6825978.3019
## 340 48657577920.3169 nan 0.0100 43367892.1237
## 360 47268142007.5242 nan 0.0100 36630023.5906
## 380 46010215296.3701 nan 0.0100 32910956.7773
## 400 44903265377.7800 nan 0.0100 -17628295.9076
## 420 43897879670.3481 nan 0.0100 44130800.0135
## 440 43089127062.3429 nan 0.0100 18950711.7623
## 460 42279678522.0066 nan 0.0100 -6769603.4006
## 480 41559548642.9627 nan 0.0100 -26668737.1781
## 500 40936587975.4558 nan 0.0100 19442530.0372
## 520 40335616882.0822 nan 0.0100 11362323.1182
## 540 39750107149.2339 nan 0.0100 -10968943.7526
## 560 39245595691.1550 nan 0.0100 -19047180.2540
## 580 38799991950.9508 nan 0.0100 9654166.0208
## 600 38360008650.4979 nan 0.0100 -28685789.8168
## 620 37932607266.6441 nan 0.0100 -18338396.1987
## 640 37472146192.6996 nan 0.0100 -12312239.7284
## 660 37068956076.2608 nan 0.0100 -1851898.7294
## 680 36667202875.4280 nan 0.0100 -336296.2978
## 700 36283437962.4626 nan 0.0100 -3806522.3741
## 720 35919459966.2580 nan 0.0100 -260778.4020
## 740 35589223535.3251 nan 0.0100 -10630368.8727
## 760 35258997349.4286 nan 0.0100 -6214440.0191
## 780 34924060426.7627 nan 0.0100 -658943.6657
## 800 34623865575.3216 nan 0.0100 -4976760.1847
## 820 34304300943.5134 nan 0.0100 6999596.2942
## 840 33982724186.9678 nan 0.0100 -29467118.7585
## 860 33700193857.6849 nan 0.0100 -7808120.8016
## 880 33397436108.1690 nan 0.0100 392032.6253
## 900 33130737654.7532 nan 0.0100 -11594268.4192
## 920 32875536730.8401 nan 0.0100 -14184506.0141
## 940 32616413200.4194 nan 0.0100 -36128678.6497
## 960 32326213363.1063 nan 0.0100 -14874283.1403
## 980 32063801812.1206 nan 0.0100 -36171317.6097
## 1000 31846000288.6906 nan 0.0100 -8419154.1015
## 1020 31608147183.7314 nan 0.0100 -22291539.8423
## 1040 31332733709.1129 nan 0.0100 8668433.8412
## 1060 31124180571.5441 nan 0.0100 -1111180.5305
## 1080 30908661850.5742 nan 0.0100 -8896328.2082
## 1100 30680306978.7297 nan 0.0100 4495070.3510
## 1120 30452996022.5516 nan 0.0100 -5810518.6084
## 1140 30259992068.9277 nan 0.0100 -17809337.3212
## 1160 30066850293.1783 nan 0.0100 -21576130.6841
## 1180 29888585275.7302 nan 0.0100 -2713451.4658
## 1200 29654472700.6593 nan 0.0100 -9291026.9437
## 1220 29442619078.7624 nan 0.0100 503976.3732
## 1240 29266100038.2313 nan 0.0100 -24073465.5768
## 1260 29092888287.7248 nan 0.0100 -8501285.5375
## 1280 28902849917.2361 nan 0.0100 -15697308.3107
## 1300 28728575520.7752 nan 0.0100 -24384413.6224
## 1320 28547561796.8730 nan 0.0100 -17066467.0477
## 1340 28377525686.0040 nan 0.0100 2307031.4150
## 1360 28209865970.5685 nan 0.0100 -7982166.1782
## 1380 28017126543.7393 nan 0.0100 -15030695.5739
## 1400 27888627066.0326 nan 0.0100 -7850981.6470
## 1420 27727517240.0463 nan 0.0100 -17732981.4631
## 1440 27528402180.6033 nan 0.0100 2081187.1409
## 1460 27399674254.4308 nan 0.0100 -17360195.4935
## 1480 27241774588.2988 nan 0.0100 -3351256.1800
## 1500 27072312399.7271 nan 0.0100 -3267235.9777
## 1520 26933165042.8257 nan 0.0100 -13534926.4062
## 1540 26797905448.5400 nan 0.0100 -1125990.9883
## 1560 26676649376.6160 nan 0.0100 594343.4479
## 1580 26542581430.6845 nan 0.0100 -12598285.0460
## 1600 26401282368.3633 nan 0.0100 197211.1527
## 1620 26274937024.1125 nan 0.0100 2627415.6849
## 1640 26122337204.8360 nan 0.0100 -1413223.2283
## 1660 25981477317.7416 nan 0.0100 -5358109.7296
## 1680 25843797907.0512 nan 0.0100 -16236918.5024
## 1700 25720660227.6729 nan 0.0100 -18901738.9520
## 1720 25591702478.3930 nan 0.0100 -9089582.1135
## 1740 25460517031.4825 nan 0.0100 -3015004.5929
## 1760 25342994169.5611 nan 0.0100 -24796366.1698
## 1780 25211150996.4503 nan 0.0100 -8712583.0999
## 1800 25086605962.7498 nan 0.0100 -5362731.5573
## 1820 24971533770.7506 nan 0.0100 -18637991.3812
## 1840 24838628692.5200 nan 0.0100 -2633026.8089
## 1860 24697513989.4043 nan 0.0100 1698193.6096
## 1880 24598159997.4027 nan 0.0100 711132.2542
## 1900 24498772300.9835 nan 0.0100 -1978646.7523
## 1920 24397087777.8445 nan 0.0100 -639213.1366
## 1940 24278291407.0712 nan 0.0100 -28779393.0393
## 1960 24159275585.8304 nan 0.0100 -3165506.4982
## 1980 24059673901.5839 nan 0.0100 -4437288.4356
## 2000 23943909942.0108 nan 0.0100 -2696445.4930
## 2020 23830938658.0668 nan 0.0100 -20821246.1348
## 2040 23720652706.5283 nan 0.0100 -10857598.4730
## 2060 23607836569.7986 nan 0.0100 -10365795.0066
## 2080 23514330809.8599 nan 0.0100 -1408308.4989
## 2100 23415909604.1453 nan 0.0100 -1448686.8700
## 2120 23326437283.7474 nan 0.0100 4289502.1789
## 2140 23232848214.0480 nan 0.0100 -8735678.8044
## 2160 23127541066.5943 nan 0.0100 -9732592.0523
## 2180 23029010754.9478 nan 0.0100 -14437922.7147
## 2200 22935101032.9803 nan 0.0100 2227471.3705
## 2220 22845776427.7793 nan 0.0100 -7662795.5561
## 2240 22776820096.6492 nan 0.0100 -13160964.1657
## 2260 22674794968.4180 nan 0.0100 -15278506.9970
## 2280 22603676718.2362 nan 0.0100 -2721073.0307
## 2300 22499366416.4495 nan 0.0100 -7453618.4884
## 2320 22397549466.1627 nan 0.0100 -301131.4866
## 2340 22276568035.1515 nan 0.0100 -971972.8795
## 2360 22184431823.2320 nan 0.0100 -2336663.0608
## 2380 22091554290.7512 nan 0.0100 -8903855.9385
## 2400 21992752080.7787 nan 0.0100 -2432452.9294
## 2420 21920267553.5207 nan 0.0100 593510.4736
## 2440 21834213273.4378 nan 0.0100 -7225378.3436
## 2460 21755253115.6493 nan 0.0100 -3649452.8268
## 2480 21682399671.1464 nan 0.0100 -2545117.8468
## 2500 21601186602.7279 nan 0.0100 -14120777.7490
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 254320988305.2506 nan 0.0010 195539901.3528
## 2 254155930002.5876 nan 0.0010 182697759.5854
## 3 253994900891.1323 nan 0.0010 184368975.6691
## 4 253826399563.6196 nan 0.0010 174476540.2988
## 5 253656329239.8051 nan 0.0010 155690345.0388
## 6 253492636543.1089 nan 0.0010 172719276.5336
## 7 253321268106.0108 nan 0.0010 161291179.2385
## 8 253150984367.5042 nan 0.0010 142496943.9725
## 9 252981834103.7204 nan 0.0010 163789799.8899
## 10 252815966932.7469 nan 0.0010 161283349.3104
## 20 251163839932.3203 nan 0.0010 156862446.3187
## 40 247973562441.4163 nan 0.0010 144392240.2912
## 60 244897417572.3786 nan 0.0010 136422909.8988
## 80 241940786916.3505 nan 0.0010 98784888.6943
## 100 239090073373.6237 nan 0.0010 154091461.3496
## 120 236325781654.8031 nan 0.0010 121366527.2762
## 140 233648922040.1790 nan 0.0010 135404544.4019
## 160 231053621392.3279 nan 0.0010 83776930.7203
## 180 228535559109.6082 nan 0.0010 127705551.1794
## 200 226109101898.0246 nan 0.0010 116380887.6146
## 220 223752986423.4193 nan 0.0010 115215190.4233
## 240 221476648137.0793 nan 0.0010 110444656.6176
## 260 219266622902.8872 nan 0.0010 107056669.7654
## 280 217090459512.5234 nan 0.0010 106265638.7423
## 300 215014580505.3058 nan 0.0010 96977499.5999
## 320 212999337898.0912 nan 0.0010 96974188.2457
## 340 211013490208.6405 nan 0.0010 94664327.3179
## 360 209105570248.4392 nan 0.0010 78176718.9505
## 380 207267807541.4579 nan 0.0010 83582046.4446
## 400 205466519252.0150 nan 0.0010 87411332.8569
## 420 203708274825.8788 nan 0.0010 78345962.3439
## 440 202017998076.9130 nan 0.0010 83616093.1743
## 460 200353273444.9110 nan 0.0010 79015270.3012
## 480 198733441315.2159 nan 0.0010 75717647.8178
## 500 197168566374.8333 nan 0.0010 63689882.2876
## 520 195645308154.1648 nan 0.0010 32967857.4542
## 540 194157603198.8098 nan 0.0010 71999959.7990
## 560 192711508685.3032 nan 0.0010 70718732.7252
## 580 191306578084.5284 nan 0.0010 62123481.0491
## 600 189944329695.3762 nan 0.0010 59808622.7121
## 620 188610274213.9455 nan 0.0010 69893873.1174
## 640 187294641336.4248 nan 0.0010 56713356.2034
## 660 186014799136.9893 nan 0.0010 60410385.2730
## 680 184760819570.5964 nan 0.0010 60164697.8869
## 700 183549292339.3599 nan 0.0010 55866268.6292
## 720 182373701803.2097 nan 0.0010 45797360.3108
## 740 181220559927.3652 nan 0.0010 32077234.7101
## 760 180090294663.9554 nan 0.0010 45835553.5156
## 780 179009270173.1241 nan 0.0010 54432109.2274
## 800 177932431111.6509 nan 0.0010 44932157.5522
## 820 176865951966.3985 nan 0.0010 47527955.9175
## 840 175827194194.6036 nan 0.0010 43633743.4640
## 860 174812171817.7458 nan 0.0010 47762584.1434
## 880 173814170144.7203 nan 0.0010 40165294.9470
## 900 172829060589.8354 nan 0.0010 51086022.7954
## 920 171872131743.0535 nan 0.0010 30675784.7412
## 940 170929861158.4181 nan 0.0010 44377548.2342
## 960 169999079512.3696 nan 0.0010 32927107.2365
## 980 169077885654.9299 nan 0.0010 46056339.6579
## 1000 168166746674.5972 nan 0.0010 37381423.9198
## 1020 167274993294.2578 nan 0.0010 34343243.9611
## 1040 166379610851.3149 nan 0.0010 40837047.1898
## 1060 165500401448.3590 nan 0.0010 26682371.4849
## 1080 164626120434.1166 nan 0.0010 31067006.1051
## 1100 163764645504.8511 nan 0.0010 40896349.4871
## 1120 162944589606.9787 nan 0.0010 40852654.7573
## 1140 162121456298.0356 nan 0.0010 40260948.4039
## 1160 161320243505.3862 nan 0.0010 39229962.0440
## 1180 160524527866.6657 nan 0.0010 14747173.9997
## 1200 159725689566.8361 nan 0.0010 37430066.8852
## 1220 158949967493.1512 nan 0.0010 32263757.9915
## 1240 158177060056.5945 nan 0.0010 34504099.4543
## 1260 157409679016.9668 nan 0.0010 30009300.0710
## 1280 156658707786.7736 nan 0.0010 34612327.9248
## 1300 155917032861.6947 nan 0.0010 33399931.1925
## 1320 155199426032.9882 nan 0.0010 34227973.6293
## 1340 154486019935.4725 nan 0.0010 36206854.6641
## 1360 153775180106.6278 nan 0.0010 24383172.6237
## 1380 153081046978.1136 nan 0.0010 27085510.8187
## 1400 152404787573.4929 nan 0.0010 30121168.6260
## 1420 151715762218.7024 nan 0.0010 25943263.2085
## 1440 151043012959.4306 nan 0.0010 32042661.7443
## 1460 150376699535.8975 nan 0.0010 24355830.7056
## 1480 149719393493.9590 nan 0.0010 25980410.2532
## 1500 149070626119.4123 nan 0.0010 5737998.0923
## 1520 148423628434.1117 nan 0.0010 30176344.6031
## 1540 147798419024.8989 nan 0.0010 17665046.3647
## 1560 147168080369.2336 nan 0.0010 26958902.3674
## 1580 146549414919.4250 nan 0.0010 27844711.2867
## 1600 145934295900.0425 nan 0.0010 17067102.3530
## 1620 145332367544.9012 nan 0.0010 29470330.9266
## 1640 144737879620.5716 nan 0.0010 32128939.0158
## 1660 144148662308.5815 nan 0.0010 27557490.3511
## 1680 143560628594.5835 nan 0.0010 30395944.0906
## 1700 142978042372.6493 nan 0.0010 4909116.5863
## 1720 142420239415.4560 nan 0.0010 27390194.0032
## 1740 141842176359.4760 nan 0.0010 25143297.2407
## 1760 141277425388.7970 nan 0.0010 18837566.3036
## 1780 140715620055.0884 nan 0.0010 17695425.4681
## 1800 140162628194.7957 nan 0.0010 8438469.3301
## 1820 139608651508.6042 nan 0.0010 16173540.4857
## 1840 139067943238.4617 nan 0.0010 18312274.8230
## 1860 138532688859.3895 nan 0.0010 22694810.4456
## 1880 138008211716.9703 nan 0.0010 27231278.9259
## 1900 137481585719.2917 nan 0.0010 8122811.3857
## 1920 136967522023.0757 nan 0.0010 21574635.0305
## 1940 136455783871.4530 nan 0.0010 25187416.2035
## 1960 135944110718.2345 nan 0.0010 19321120.0853
## 1980 135444607069.0560 nan 0.0010 18529163.8525
## 2000 134944775085.1507 nan 0.0010 24440725.3195
## 2020 134457474213.4780 nan 0.0010 16041407.4651
## 2040 133975481290.2763 nan 0.0010 9483221.6951
## 2060 133499910920.1198 nan 0.0010 13261118.8301
## 2080 133027012779.4785 nan 0.0010 18805695.8796
## 2100 132559162576.2519 nan 0.0010 2857338.5693
## 2120 132095621953.3784 nan 0.0010 23684633.8604
## 2140 131643168030.0307 nan 0.0010 18237304.0953
## 2160 131185830959.5849 nan 0.0010 19236413.2421
## 2180 130735613300.0226 nan 0.0010 22354993.9030
## 2200 130298156809.5318 nan 0.0010 18877574.1020
## 2220 129869021902.9300 nan 0.0010 15554334.0419
## 2240 129439014367.6010 nan 0.0010 1703762.4694
## 2260 129003140923.4312 nan 0.0010 14335675.8404
## 2280 128578750339.0226 nan 0.0010 13886479.5482
## 2300 128161328418.3302 nan 0.0010 17354408.9081
## 2320 127748209534.3278 nan 0.0010 21571731.1813
## 2340 127345865075.4942 nan 0.0010 20616515.9093
## 2360 126943011331.0771 nan 0.0010 20271798.3729
## 2380 126542613124.2807 nan 0.0010 1571888.8600
## 2400 126148205226.8974 nan 0.0010 14173708.5859
## 2420 125743286122.6029 nan 0.0010 10770679.2918
## 2440 125347768516.9764 nan 0.0010 10925426.0485
## 2460 124949743012.8501 nan 0.0010 13979365.2139
## 2480 124560581786.2185 nan 0.0010 16945107.6650
## 2500 124172608068.5910 nan 0.0010 15768095.2352
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 254217125702.2489 nan 0.0010 247910543.2764
## 2 253954361472.2008 nan 0.0010 253084450.1695
## 3 253693661077.4642 nan 0.0010 238868769.8436
## 4 253413225047.5937 nan 0.0010 228199398.3783
## 5 253153003229.3141 nan 0.0010 232391356.9051
## 6 252875231359.2800 nan 0.0010 254249574.1073
## 7 252617985395.4264 nan 0.0010 229333178.5651
## 8 252365373043.4886 nan 0.0010 255413881.7122
## 9 252092548761.3795 nan 0.0010 270540564.5863
## 10 251817929642.9099 nan 0.0010 244456553.0598
## 20 249226552779.2238 nan 0.0010 221829918.7713
## 40 244144925350.6748 nan 0.0010 244611910.5683
## 60 239231332333.9500 nan 0.0010 270851743.0800
## 80 234527980336.3553 nan 0.0010 239175437.0367
## 100 229929082797.8194 nan 0.0010 175605867.6440
## 120 225489951477.7866 nan 0.0010 174782631.6509
## 140 221164628872.3481 nan 0.0010 117675020.8811
## 160 217009467921.7065 nan 0.0010 166339322.0825
## 180 213030750840.7280 nan 0.0010 182834999.3841
## 200 209131061079.8277 nan 0.0010 183904587.2855
## 220 205453181754.9663 nan 0.0010 186511623.7657
## 240 201836994247.5377 nan 0.0010 161779742.9611
## 260 198337260126.5175 nan 0.0010 131311233.8343
## 280 194986788377.2067 nan 0.0010 129384948.9284
## 300 191681302471.6976 nan 0.0010 166544841.8026
## 320 188464219193.7577 nan 0.0010 147915629.2854
## 340 185377206479.8262 nan 0.0010 150289143.7751
## 360 182344140397.6641 nan 0.0010 128133880.1480
## 380 179402396153.7516 nan 0.0010 91230937.3147
## 400 176633027102.4584 nan 0.0010 145100807.3455
## 420 173830495430.2856 nan 0.0010 146290260.5960
## 440 171142240061.3401 nan 0.0010 174234929.9206
## 460 168532932642.7242 nan 0.0010 93905118.3288
## 480 166047952340.6323 nan 0.0010 118418978.0935
## 500 163607554461.0491 nan 0.0010 135831244.5583
## 520 161237461374.2272 nan 0.0010 100639797.4090
## 540 158960522943.1919 nan 0.0010 110579089.7106
## 560 156737762212.2325 nan 0.0010 99011858.4158
## 580 154544096964.6869 nan 0.0010 93163717.8852
## 600 152414736270.1389 nan 0.0010 81196863.9483
## 620 150354806028.9202 nan 0.0010 77531265.6995
## 640 148339571490.9506 nan 0.0010 84557373.9071
## 660 146382966461.5698 nan 0.0010 88460114.4223
## 680 144444167708.8759 nan 0.0010 104311211.1797
## 700 142582122917.5735 nan 0.0010 103770544.0997
## 720 140768602981.3584 nan 0.0010 67679306.6455
## 740 139018957860.5074 nan 0.0010 64132254.4725
## 760 137270088554.6167 nan 0.0010 44606829.5846
## 780 135583806312.7711 nan 0.0010 81581748.7502
## 800 133955454460.4784 nan 0.0010 66015955.5977
## 820 132340870803.5708 nan 0.0010 61127446.5746
## 840 130758960150.1159 nan 0.0010 83738147.9171
## 860 129209341789.4083 nan 0.0010 57072250.0831
## 880 127733269305.1826 nan 0.0010 65866140.3485
## 900 126260925013.1687 nan 0.0010 72924310.9555
## 920 124834736673.0887 nan 0.0010 52214313.6803
## 940 123419274477.9087 nan 0.0010 49886306.7774
## 960 122036924639.5015 nan 0.0010 66169045.7902
## 980 120678742236.0583 nan 0.0010 69377817.3009
## 1000 119346938061.7236 nan 0.0010 59723769.5536
## 1020 118074908957.7236 nan 0.0010 68512738.1869
## 1040 116764094805.0366 nan 0.0010 85264066.9636
## 1060 115520017006.3669 nan 0.0010 63058007.6289
## 1080 114340928346.7485 nan 0.0010 37596051.8690
## 1100 113171791150.0280 nan 0.0010 40888615.0330
## 1120 112041065491.6388 nan 0.0010 64130065.4766
## 1140 110915053821.4983 nan 0.0010 59167111.1581
## 1160 109790907318.2398 nan 0.0010 56603703.0052
## 1180 108721254123.1773 nan 0.0010 60798051.6893
## 1200 107674904077.4084 nan 0.0010 35275474.3350
## 1220 106671258979.2040 nan 0.0010 32992931.8322
## 1240 105667045070.4070 nan 0.0010 37574843.0467
## 1260 104660190052.1707 nan 0.0010 41906639.1954
## 1280 103668844177.2175 nan 0.0010 47646558.6473
## 1300 102704514667.1997 nan 0.0010 29947917.4976
## 1320 101751555059.6068 nan 0.0010 51318974.6951
## 1340 100825081366.0438 nan 0.0010 53527678.4433
## 1360 99912732255.6327 nan 0.0010 29481628.3808
## 1380 99029840120.7560 nan 0.0010 30773252.0479
## 1400 98147361276.3802 nan 0.0010 20780947.6819
## 1420 97287662422.6232 nan 0.0010 36512422.1968
## 1440 96450424989.2160 nan 0.0010 31667106.7733
## 1460 95621901760.5637 nan 0.0010 36428076.8398
## 1480 94787479907.8859 nan 0.0010 41654097.0580
## 1500 93994152386.7962 nan 0.0010 22589295.7911
## 1520 93222907081.0876 nan 0.0010 44953823.7738
## 1540 92427828165.8925 nan 0.0010 36306380.4491
## 1560 91664263274.6539 nan 0.0010 23174610.0262
## 1580 90901025511.0114 nan 0.0010 34906838.4587
## 1600 90142846689.1315 nan 0.0010 24075120.6118
## 1620 89412878121.1179 nan 0.0010 38114065.6214
## 1640 88683720743.1541 nan 0.0010 33870258.7620
## 1660 87986039422.9640 nan 0.0010 31426197.3199
## 1680 87294492520.5773 nan 0.0010 35077828.1611
## 1700 86631047199.8201 nan 0.0010 19920493.9715
## 1720 85947394522.4501 nan 0.0010 33983833.6250
## 1740 85279688109.0484 nan 0.0010 25511318.5476
## 1760 84632276317.3269 nan 0.0010 17524571.1836
## 1780 83999358221.6731 nan 0.0010 21175020.0030
## 1800 83366326798.3771 nan 0.0010 28402999.1964
## 1820 82706048021.0262 nan 0.0010 15486625.0030
## 1840 82056646047.0207 nan 0.0010 15610261.6960
## 1860 81449813532.8734 nan 0.0010 23104598.4759
## 1880 80850945349.8495 nan 0.0010 13765032.8486
## 1900 80266885759.2053 nan 0.0010 25513843.2824
## 1920 79700773154.0456 nan 0.0010 22512833.7966
## 1940 79132018539.4487 nan 0.0010 19495263.3977
## 1960 78584483923.8841 nan 0.0010 17549630.0588
## 1980 78016447724.1073 nan 0.0010 22177985.0180
## 2000 77478975931.2788 nan 0.0010 21603732.7443
## 2020 76949292472.8601 nan 0.0010 21553748.0871
## 2040 76402047169.6511 nan 0.0010 19905245.4973
## 2060 75890299864.3242 nan 0.0010 15462841.5151
## 2080 75396282101.2054 nan 0.0010 13914036.8301
## 2100 74903401227.9440 nan 0.0010 24614315.6336
## 2120 74406242837.6019 nan 0.0010 31483803.0053
## 2140 73909006635.4057 nan 0.0010 18137308.1850
## 2160 73440536590.1063 nan 0.0010 22085324.5273
## 2180 72970080568.9292 nan 0.0010 28752473.1804
## 2200 72499415912.4789 nan 0.0010 29078802.0711
## 2220 72035590521.5546 nan 0.0010 17334663.9037
## 2240 71569919450.7418 nan 0.0010 14069491.6399
## 2260 71113619896.5466 nan 0.0010 14788923.0149
## 2280 70674255969.0700 nan 0.0010 16052069.9537
## 2300 70222679852.5132 nan 0.0010 28546242.6492
## 2320 69805001482.9880 nan 0.0010 18002638.2723
## 2340 69373020833.4860 nan 0.0010 21902237.6361
## 2360 68967783675.5667 nan 0.0010 17106136.8492
## 2380 68551076090.0806 nan 0.0010 10385088.7240
## 2400 68151860624.8945 nan 0.0010 23919457.5172
## 2420 67742957352.8617 nan 0.0010 14267352.9692
## 2440 67337277948.9479 nan 0.0010 11535993.8118
## 2460 66963190624.3852 nan 0.0010 7776545.4339
## 2480 66559885891.4947 nan 0.0010 15605872.4005
## 2500 66195756169.2926 nan 0.0010 10032966.4941
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 254201412032.3622 nan 0.0010 295984604.2870
## 2 253886935694.4654 nan 0.0010 242711803.5238
## 3 253585268156.1608 nan 0.0010 315363234.7406
## 4 253273671958.3667 nan 0.0010 301034432.1015
## 5 252974443519.3840 nan 0.0010 325704115.8821
## 6 252655979245.1301 nan 0.0010 304958177.2902
## 7 252350544825.5786 nan 0.0010 266200593.3192
## 8 252050864819.5560 nan 0.0010 276183293.0676
## 9 251741093009.7539 nan 0.0010 271409743.1505
## 10 251429676637.0237 nan 0.0010 343874535.9678
## 20 248454059585.2086 nan 0.0010 264867587.5655
## 40 242579931495.5637 nan 0.0010 315573410.2456
## 60 236945865204.6135 nan 0.0010 253065160.4892
## 80 231511937185.5912 nan 0.0010 240887535.5460
## 100 226283233035.9625 nan 0.0010 204679895.2799
## 120 221275113231.8883 nan 0.0010 274069760.2586
## 140 216381164715.0445 nan 0.0010 198756318.9456
## 160 211676735495.6213 nan 0.0010 236583151.9839
## 180 207109106744.8017 nan 0.0010 239523616.9032
## 200 202703989396.9466 nan 0.0010 183737242.9820
## 220 198434813101.6887 nan 0.0010 198835963.3488
## 240 194337813668.3159 nan 0.0010 205845296.3443
## 260 190367222883.6429 nan 0.0010 178090558.1964
## 280 186487259140.3680 nan 0.0010 195276433.5593
## 300 182766865215.1400 nan 0.0010 163702504.7342
## 320 179121370923.3870 nan 0.0010 157092928.6384
## 340 175570974499.9893 nan 0.0010 153633827.7485
## 360 172202480115.5652 nan 0.0010 134207720.4950
## 380 168916079293.8015 nan 0.0010 174887284.6018
## 400 165738378270.6202 nan 0.0010 124862748.5169
## 420 162640625099.0601 nan 0.0010 126644805.1259
## 440 159610112106.7677 nan 0.0010 122679309.8680
## 460 156709533389.8992 nan 0.0010 99076767.9192
## 480 153873076544.9483 nan 0.0010 130546504.4575
## 500 151126077113.6710 nan 0.0010 116724755.6028
## 520 148468561530.5559 nan 0.0010 150708313.5983
## 540 145882331714.7410 nan 0.0010 118889791.4006
## 560 143386402361.6946 nan 0.0010 122408912.1159
## 580 140944820831.3279 nan 0.0010 106990973.8902
## 600 138559924052.8083 nan 0.0010 126709926.7281
## 620 136232049432.8987 nan 0.0010 97859477.7028
## 640 134029848423.5968 nan 0.0010 100131704.2365
## 660 131842544964.9091 nan 0.0010 87192875.5566
## 680 129760814684.9487 nan 0.0010 99839848.1101
## 700 127691834530.4123 nan 0.0010 105140252.6829
## 720 125685827425.5543 nan 0.0010 120978152.7934
## 740 123702677445.0550 nan 0.0010 82779746.6739
## 760 121813225741.0613 nan 0.0010 68615373.1790
## 780 120014069611.4109 nan 0.0010 99671839.8341
## 800 118227352849.7409 nan 0.0010 58450721.3929
## 820 116508670358.5223 nan 0.0010 77035856.9269
## 840 114812095206.5937 nan 0.0010 90316283.8328
## 860 113170966983.7885 nan 0.0010 75407692.2778
## 880 111579579923.4300 nan 0.0010 76092825.1364
## 900 110030857611.0473 nan 0.0010 50946749.6128
## 920 108514599058.0407 nan 0.0010 62240388.9777
## 940 107071269957.3310 nan 0.0010 90957654.4320
## 960 105617617602.6252 nan 0.0010 67735233.2331
## 980 104198672539.9943 nan 0.0010 46799856.7869
## 1000 102824510013.5671 nan 0.0010 77267858.0089
## 1020 101475569022.2369 nan 0.0010 49450758.4565
## 1040 100168224942.0780 nan 0.0010 59522177.3868
## 1060 98882795745.4973 nan 0.0010 61659450.8762
## 1080 97645825506.6526 nan 0.0010 65007113.3965
## 1100 96429557603.7471 nan 0.0010 38114973.2543
## 1120 95239733356.0915 nan 0.0010 50702763.5408
## 1140 94064322865.1844 nan 0.0010 60438344.9178
## 1160 92932975928.7311 nan 0.0010 49902546.5995
## 1180 91821675221.2196 nan 0.0010 44050552.7324
## 1200 90743337212.1522 nan 0.0010 34979171.5694
## 1220 89678876090.4753 nan 0.0010 32883223.0606
## 1240 88640614665.5236 nan 0.0010 46914433.7227
## 1260 87631484197.8506 nan 0.0010 35234462.2471
## 1280 86656530584.9448 nan 0.0010 42853784.3625
## 1300 85695750314.6514 nan 0.0010 41020499.0899
## 1320 84749925555.4021 nan 0.0010 46906321.8892
## 1340 83838610918.3701 nan 0.0010 45535088.9495
## 1360 82943296412.7288 nan 0.0010 35774297.4906
## 1380 82076672758.4084 nan 0.0010 41538923.5929
## 1400 81210559011.2439 nan 0.0010 35284703.8389
## 1420 80354357080.8699 nan 0.0010 29361056.6401
## 1440 79543961993.6457 nan 0.0010 35247163.2070
## 1460 78751759839.0888 nan 0.0010 49708629.0295
## 1480 77977965149.6661 nan 0.0010 17982699.2938
## 1500 77229339766.9569 nan 0.0010 23447937.9738
## 1520 76490856985.6431 nan 0.0010 32878943.5029
## 1540 75759191828.2671 nan 0.0010 25000621.6349
## 1560 75006066503.2148 nan 0.0010 22941298.8561
## 1580 74300666413.8956 nan 0.0010 43937546.9350
## 1600 73604283020.3001 nan 0.0010 17247925.5617
## 1620 72934722115.5371 nan 0.0010 28587171.3662
## 1640 72274020177.4370 nan 0.0010 23425812.7147
## 1660 71638941188.1898 nan 0.0010 25937169.4554
## 1680 71020410101.9804 nan 0.0010 26787952.5645
## 1700 70389277620.7586 nan 0.0010 30025124.3717
## 1720 69775657572.0884 nan 0.0010 24401619.0756
## 1740 69168736805.3537 nan 0.0010 24742155.7961
## 1760 68570095752.6389 nan 0.0010 26522947.2700
## 1780 67994940733.6222 nan 0.0010 20361663.1413
## 1800 67429418568.3142 nan 0.0010 24036703.9941
## 1820 66876531099.0417 nan 0.0010 29923371.4412
## 1840 66334981560.5262 nan 0.0010 16528318.1967
## 1860 65789048544.0058 nan 0.0010 11829303.0539
## 1880 65249668805.4469 nan 0.0010 19249675.9791
## 1900 64721359595.8334 nan 0.0010 20738945.6628
## 1920 64199194726.5230 nan 0.0010 23691785.9151
## 1940 63687180627.9706 nan 0.0010 23753035.0327
## 1960 63205809019.1163 nan 0.0010 25750822.2718
## 1980 62714273555.6962 nan 0.0010 23240696.8980
## 2000 62223619324.3463 nan 0.0010 11324034.6956
## 2020 61757416211.5851 nan 0.0010 20749070.9348
## 2040 61311428826.7401 nan 0.0010 17997647.2624
## 2060 60862363604.4340 nan 0.0010 16799907.1333
## 2080 60412575682.9491 nan 0.0010 14786696.9960
## 2100 59965545398.3662 nan 0.0010 27911270.4002
## 2120 59551973247.9451 nan 0.0010 13992082.5356
## 2140 59144651251.5863 nan 0.0010 10015423.7887
## 2160 58737144305.0546 nan 0.0010 14338158.8050
## 2180 58335963479.8484 nan 0.0010 21627387.1182
## 2200 57944024037.6680 nan 0.0010 16266986.0661
## 2220 57561754880.4997 nan 0.0010 10556209.7868
## 2240 57177452467.1729 nan 0.0010 15132862.4069
## 2260 56807580810.8020 nan 0.0010 14433112.1674
## 2280 56450508854.9104 nan 0.0010 10794664.2699
## 2300 56085689057.1768 nan 0.0010 22258803.2654
## 2320 55732406162.2471 nan 0.0010 14457540.4328
## 2340 55375180223.5012 nan 0.0010 16950247.2333
## 2360 55035356751.5324 nan 0.0010 20027713.0440
## 2380 54695769162.8537 nan 0.0010 16601093.6179
## 2400 54370309821.7853 nan 0.0010 14286612.4567
## 2420 54048732846.7753 nan 0.0010 9860317.8796
## 2440 53743100775.6800 nan 0.0010 21306211.8942
## 2460 53437224168.2075 nan 0.0010 7865985.4387
## 2480 53136111785.5669 nan 0.0010 4031990.1204
## 2500 52834997662.8097 nan 0.0010 12590766.6785
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 252787374458.8531 nan 0.0100 1590769995.9375
## 2 251137275051.2661 nan 0.0100 1610063788.5140
## 3 249546564495.3589 nan 0.0100 1596436472.0446
## 4 247888541103.3889 nan 0.0100 1519068134.8392
## 5 246256711033.0157 nan 0.0100 1399546252.4225
## 6 244743764929.0181 nan 0.0100 1377841482.0959
## 7 243238968830.3551 nan 0.0100 1622061098.3487
## 8 241791597056.7202 nan 0.0100 1425553870.6041
## 9 240283521742.7418 nan 0.0100 1295510914.4666
## 10 238899985770.0657 nan 0.0100 1550114254.1274
## 20 226045507418.0121 nan 0.0100 1249614157.2908
## 40 205389463607.3458 nan 0.0100 811647943.5255
## 60 190010730757.8329 nan 0.0100 560360449.8136
## 80 177794500848.1733 nan 0.0100 523410695.0834
## 100 167918360458.3749 nan 0.0100 415898809.3501
## 120 159566416328.7628 nan 0.0100 392396823.2282
## 140 152217724518.9972 nan 0.0100 183718860.9535
## 160 145747961932.9372 nan 0.0100 225645062.5941
## 180 139883925763.5922 nan 0.0100 172139091.6060
## 200 134728464358.5127 nan 0.0100 183478606.1760
## 220 130062160635.6239 nan 0.0100 190407872.6112
## 240 125875804448.7773 nan 0.0100 90016749.9729
## 260 122109338624.5092 nan 0.0100 101327868.8201
## 280 118679858994.1123 nan 0.0100 48682665.5660
## 300 115522256006.8418 nan 0.0100 145268297.8731
## 320 112590830770.0961 nan 0.0100 139717930.3121
## 340 109918334266.4406 nan 0.0100 126832915.2835
## 360 107487474189.7598 nan 0.0100 106777222.9053
## 380 105252188403.6939 nan 0.0100 82852119.4473
## 400 103145147310.0145 nan 0.0100 57924971.1737
## 420 101146229136.1596 nan 0.0100 100790411.7994
## 440 99310156360.7369 nan 0.0100 50416357.2401
## 460 97613195493.5421 nan 0.0100 72201671.0376
## 480 96054320806.7675 nan 0.0100 24641069.5200
## 500 94619542019.0909 nan 0.0100 28219021.9782
## 520 93254596094.9098 nan 0.0100 68610879.6192
## 540 91971796092.1621 nan 0.0100 -12805599.3882
## 560 90778265539.8895 nan 0.0100 46086485.0266
## 580 89661480054.0226 nan 0.0100 21603493.0175
## 600 88633927266.4330 nan 0.0100 48607130.1876
## 620 87639573770.5919 nan 0.0100 36610731.7422
## 640 86729733118.6677 nan 0.0100 34846332.9076
## 660 85885451948.1386 nan 0.0100 -64601505.6665
## 680 85103064068.2738 nan 0.0100 36782565.8979
## 700 84356559939.6455 nan 0.0100 27591082.3892
## 720 83668363984.6447 nan 0.0100 21704441.7769
## 740 83008461668.8123 nan 0.0100 11670106.9086
## 760 82413685076.7005 nan 0.0100 27560985.7096
## 780 81847695646.8687 nan 0.0100 9944207.1792
## 800 81314100875.7736 nan 0.0100 22003752.8248
## 820 80815828046.9169 nan 0.0100 19843481.1505
## 840 80350631269.8487 nan 0.0100 20291605.3363
## 860 79888928922.9150 nan 0.0100 -305077.6518
## 880 79458974292.7412 nan 0.0100 7782992.2006
## 900 79073584052.5331 nan 0.0100 -24627797.9159
## 920 78680979628.6694 nan 0.0100 6614097.0188
## 940 78310354535.8916 nan 0.0100 14044345.3201
## 960 77979426652.7486 nan 0.0100 15765008.4822
## 980 77669898358.3661 nan 0.0100 -26559067.9479
## 1000 77376445517.8908 nan 0.0100 -39841112.5429
## 1020 77097073185.1823 nan 0.0100 -4513077.3611
## 1040 76830555785.9251 nan 0.0100 13225403.0023
## 1060 76552372694.0251 nan 0.0100 10341566.8438
## 1080 76302263309.2470 nan 0.0100 9322644.8598
## 1100 76059208207.2355 nan 0.0100 -20085812.3628
## 1120 75827399278.6327 nan 0.0100 -30891655.8339
## 1140 75601751942.3985 nan 0.0100 10408105.8003
## 1160 75400797301.8515 nan 0.0100 4638137.0920
## 1180 75186303566.5403 nan 0.0100 10394075.2287
## 1200 75021251349.7437 nan 0.0100 -29783057.6884
## 1220 74842090192.4431 nan 0.0100 -10550343.1692
## 1240 74665992351.2468 nan 0.0100 8659322.9432
## 1260 74503847422.3889 nan 0.0100 5958447.3585
## 1280 74354801787.9086 nan 0.0100 -8270215.5868
## 1300 74202745168.4961 nan 0.0100 6060090.0071
## 1320 74045933344.1945 nan 0.0100 8311405.8858
## 1340 73892125319.7408 nan 0.0100 7967172.3734
## 1360 73779789156.3730 nan 0.0100 -23587543.3905
## 1380 73626025937.3428 nan 0.0100 6458812.0071
## 1400 73509067300.4948 nan 0.0100 2775868.8862
## 1420 73380211867.4601 nan 0.0100 -20875693.8806
## 1440 73244827638.8742 nan 0.0100 5712068.7608
## 1460 73130960704.7547 nan 0.0100 5144301.9448
## 1480 73006180303.4137 nan 0.0100 3626547.4625
## 1500 72905515962.9520 nan 0.0100 -26682911.6960
## 1520 72803568138.7758 nan 0.0100 -17182089.0045
## 1540 72703819326.6158 nan 0.0100 -8960397.9610
## 1560 72606068462.4046 nan 0.0100 784836.8586
## 1580 72519658154.8235 nan 0.0100 2218974.4297
## 1600 72415031366.6306 nan 0.0100 3602094.1852
## 1620 72330166184.7750 nan 0.0100 4033082.3874
## 1640 72242466260.4527 nan 0.0100 3677798.1563
## 1660 72168335342.7875 nan 0.0100 -37096931.6441
## 1680 72077096076.4430 nan 0.0100 -6729842.2186
## 1700 71992031025.2677 nan 0.0100 1131154.4829
## 1720 71910532343.5550 nan 0.0100 -4237413.7864
## 1740 71839847957.1244 nan 0.0100 -31712035.0656
## 1760 71775870531.6480 nan 0.0100 -36501516.4799
## 1780 71707773088.9730 nan 0.0100 -22243791.9465
## 1800 71627703792.1074 nan 0.0100 -1127780.8624
## 1820 71559565702.8041 nan 0.0100 -12262286.1648
## 1840 71477872807.1133 nan 0.0100 2898082.9890
## 1860 71405027024.9323 nan 0.0100 -11007910.5247
## 1880 71343871186.5778 nan 0.0100 -17922457.5719
## 1900 71255791797.9301 nan 0.0100 1588594.6080
## 1920 71195139658.0885 nan 0.0100 -2693821.4703
## 1940 71131401088.8470 nan 0.0100 -14240557.9018
## 1960 71064787430.6051 nan 0.0100 -14555.5462
## 1980 70992567363.0986 nan 0.0100 -27948406.7476
## 2000 70923290601.3587 nan 0.0100 1348398.1474
## 2020 70852494146.0264 nan 0.0100 1900017.8701
## 2040 70793825804.6052 nan 0.0100 2638923.1279
## 2060 70733439058.2473 nan 0.0100 2649101.2138
## 2080 70682157709.4150 nan 0.0100 -68644533.8218
## 2100 70625519731.0744 nan 0.0100 -9344973.9999
## 2120 70560713146.4592 nan 0.0100 -4878323.9722
## 2140 70501221584.6854 nan 0.0100 -13725028.2709
## 2160 70447152876.8686 nan 0.0100 -10492536.0296
## 2180 70390448623.3467 nan 0.0100 -56070808.1713
## 2200 70334798944.8195 nan 0.0100 -9355927.5679
## 2220 70288376346.6673 nan 0.0100 -16337294.7665
## 2240 70234763814.9968 nan 0.0100 -21448020.8226
## 2260 70182834922.0582 nan 0.0100 -11342647.0212
## 2280 70137346125.3818 nan 0.0100 -23023110.9523
## 2300 70098044360.3082 nan 0.0100 -37199550.4084
## 2320 70035967111.9903 nan 0.0100 -10538672.5561
## 2340 69989369480.1557 nan 0.0100 -20127327.8562
## 2360 69942053961.5591 nan 0.0100 682954.5968
## 2380 69894870036.7095 nan 0.0100 -21040265.2529
## 2400 69847964432.7840 nan 0.0100 -5260893.0174
## 2420 69809865900.7592 nan 0.0100 -1953466.2892
## 2440 69759703637.9373 nan 0.0100 1419097.9256
## 2460 69711833370.4469 nan 0.0100 -6235573.4248
## 2480 69661573911.9369 nan 0.0100 -9251502.9741
## 2500 69618203792.8249 nan 0.0100 -9972214.7066
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 251794454790.5200 nan 0.0100 2264268394.6653
## 2 249224472216.0648 nan 0.0100 2789034542.7948
## 3 246812491349.1285 nan 0.0100 2979049568.1535
## 4 244339878194.7687 nan 0.0100 2368282094.4852
## 5 241895170842.0614 nan 0.0100 2325933522.8298
## 6 239512186624.1017 nan 0.0100 2585898149.9273
## 7 237094386186.7283 nan 0.0100 2550043456.6394
## 8 234636856012.8992 nan 0.0100 2408391782.9801
## 9 232229116234.8692 nan 0.0100 2224521815.1981
## 10 230021871150.2205 nan 0.0100 1744637751.9341
## 20 209162516580.7289 nan 0.0100 1442022770.5970
## 40 176409223681.9998 nan 0.0100 1386916341.3687
## 60 152478633332.8065 nan 0.0100 680615545.8959
## 80 133607262068.8354 nan 0.0100 797515504.9690
## 100 118752085718.6219 nan 0.0100 672050294.3015
## 120 107335984556.7810 nan 0.0100 370272854.5484
## 140 97865768020.7977 nan 0.0100 402195637.8021
## 160 90044304416.0967 nan 0.0100 321876799.6393
## 180 83417949679.7165 nan 0.0100 173069414.4096
## 200 77622929502.2843 nan 0.0100 267189922.4072
## 220 72629782897.9129 nan 0.0100 243094808.3783
## 240 68343025999.5293 nan 0.0100 165741473.8880
## 260 64444576693.5213 nan 0.0100 172545545.7401
## 280 61091242433.2626 nan 0.0100 158731203.2553
## 300 58277820786.1016 nan 0.0100 62139040.2774
## 320 55917546320.3666 nan 0.0100 43915505.0851
## 340 53896491325.7872 nan 0.0100 106847971.6760
## 360 52079563435.4424 nan 0.0100 52638638.4488
## 380 50524523951.2280 nan 0.0100 -12575807.9458
## 400 49239194836.2731 nan 0.0100 2731226.1164
## 420 48004361910.4418 nan 0.0100 -9898438.4511
## 440 46944329545.2259 nan 0.0100 19213162.5627
## 460 45923087768.1417 nan 0.0100 51197310.9186
## 480 45068800484.7092 nan 0.0100 -1957626.7015
## 500 44307604107.7763 nan 0.0100 8519306.7053
## 520 43613933647.7130 nan 0.0100 23164648.1644
## 540 42982937855.6202 nan 0.0100 21617747.7628
## 560 42414641012.8216 nan 0.0100 24481984.4522
## 580 41901844566.8134 nan 0.0100 6185422.2852
## 600 41453917678.8540 nan 0.0100 4966593.5837
## 620 41018945487.6007 nan 0.0100 -11473356.5297
## 640 40605949861.9900 nan 0.0100 -98463.8345
## 660 40251535241.5456 nan 0.0100 -7545507.0682
## 680 39884273389.4886 nan 0.0100 -12323399.3490
## 700 39542738389.6094 nan 0.0100 13272112.0363
## 720 39221019766.4299 nan 0.0100 8057272.3947
## 740 38929701653.9540 nan 0.0100 12473445.9082
## 760 38612201458.4873 nan 0.0100 -27755432.2343
## 780 38355370947.6306 nan 0.0100 8742859.8455
## 800 38098099722.7392 nan 0.0100 4925262.9695
## 820 37848516264.4835 nan 0.0100 -41125119.8622
## 840 37620204788.4933 nan 0.0100 -2964105.7984
## 860 37395746452.0719 nan 0.0100 -15739334.5487
## 880 37155876143.3057 nan 0.0100 2036625.0545
## 900 36940065381.6029 nan 0.0100 -1786950.3000
## 920 36726501271.2574 nan 0.0100 -9487803.6095
## 940 36522362826.8521 nan 0.0100 -1659717.5518
## 960 36315103768.9733 nan 0.0100 -6437696.3690
## 980 36067855118.2666 nan 0.0100 1522506.8118
## 1000 35888114418.7429 nan 0.0100 -61883466.5323
## 1020 35697267895.2248 nan 0.0100 -8512628.1437
## 1040 35475645893.9577 nan 0.0100 -20562730.1458
## 1060 35301242382.6305 nan 0.0100 9471075.4922
## 1080 35097551249.8512 nan 0.0100 -21036191.9889
## 1100 34916939511.2775 nan 0.0100 -9868314.4987
## 1120 34774807384.0373 nan 0.0100 98361.4436
## 1140 34595807268.3935 nan 0.0100 -17152449.9255
## 1160 34437587249.3000 nan 0.0100 3032057.3279
## 1180 34296193094.7842 nan 0.0100 -2343759.9172
## 1200 34127444647.8630 nan 0.0100 2068355.0557
## 1220 33965624360.9571 nan 0.0100 -12347254.0527
## 1240 33806379543.4940 nan 0.0100 -11489353.3900
## 1260 33647643393.9465 nan 0.0100 1500514.6342
## 1280 33458819464.9382 nan 0.0100 -22882021.7979
## 1300 33282205300.7822 nan 0.0100 278477.9784
## 1320 33130029520.5865 nan 0.0100 -1566767.1362
## 1340 32996800337.5576 nan 0.0100 -7499812.5228
## 1360 32836711976.0780 nan 0.0100 -27691715.4347
## 1380 32675506904.8408 nan 0.0100 3692550.1366
## 1400 32532348437.2425 nan 0.0100 -11057531.6745
## 1420 32368114458.7531 nan 0.0100 -20671559.3757
## 1440 32226159997.7339 nan 0.0100 -13723785.0754
## 1460 32114168416.1236 nan 0.0100 -11958895.2890
## 1480 31985509263.0669 nan 0.0100 -18013600.1978
## 1500 31834595532.4162 nan 0.0100 3253006.1854
## 1520 31713055966.2615 nan 0.0100 -10180628.4391
## 1540 31575876291.5363 nan 0.0100 -1273353.8203
## 1560 31440867333.3145 nan 0.0100 -11883454.0245
## 1580 31315017735.5811 nan 0.0100 -10654943.7523
## 1600 31150618211.6759 nan 0.0100 -5462489.0930
## 1620 31016638496.2183 nan 0.0100 -5321589.1007
## 1640 30910600804.1710 nan 0.0100 -9685352.2357
## 1660 30820376674.6432 nan 0.0100 -5610758.0559
## 1680 30703242040.4597 nan 0.0100 -4628015.6881
## 1700 30606491442.6801 nan 0.0100 -8461109.5427
## 1720 30465384591.6632 nan 0.0100 -2610412.7214
## 1740 30377609225.5360 nan 0.0100 -13003559.0720
## 1760 30259064779.3263 nan 0.0100 214426.7181
## 1780 30153780942.5489 nan 0.0100 -1550556.2518
## 1800 30042168723.3408 nan 0.0100 -10341541.1128
## 1820 29934792853.9528 nan 0.0100 -15686361.5020
## 1840 29808934824.8420 nan 0.0100 -35298655.1703
## 1860 29719916211.1780 nan 0.0100 -13946134.4474
## 1880 29625247395.5050 nan 0.0100 -16010362.3299
## 1900 29540999718.7477 nan 0.0100 -13859140.4695
## 1920 29460125499.3119 nan 0.0100 -10098865.2992
## 1940 29340597162.9782 nan 0.0100 -10096224.9691
## 1960 29238635800.6870 nan 0.0100 -7447793.7534
## 1980 29146752373.6651 nan 0.0100 -18125441.8551
## 2000 29029808660.0588 nan 0.0100 786349.0993
## 2020 28934802143.9225 nan 0.0100 -19236261.4687
## 2040 28825544416.3188 nan 0.0100 1192837.8135
## 2060 28722549393.2134 nan 0.0100 -457722.7986
## 2080 28631380069.9427 nan 0.0100 -2153858.2093
## 2100 28519936173.3506 nan 0.0100 -7137621.1312
## 2120 28417977330.4009 nan 0.0100 -2700777.1118
## 2140 28334073862.0930 nan 0.0100 -3351506.1538
## 2160 28253028656.0831 nan 0.0100 -383916.5107
## 2180 28160123133.8798 nan 0.0100 870381.3837
## 2200 28043368820.0770 nan 0.0100 -36251583.4693
## 2220 27943903445.0181 nan 0.0100 -12424657.0214
## 2240 27855346768.2325 nan 0.0100 -9451947.6992
## 2260 27756797773.1947 nan 0.0100 -8986872.7683
## 2280 27688689035.8988 nan 0.0100 -6701231.8416
## 2300 27581637092.4151 nan 0.0100 -5945003.9547
## 2320 27511251439.3971 nan 0.0100 -2392000.5072
## 2340 27439505913.5400 nan 0.0100 -10043327.5128
## 2360 27360441469.1825 nan 0.0100 -23966706.4962
## 2380 27277688344.6005 nan 0.0100 -28549087.2232
## 2400 27211664183.3571 nan 0.0100 -7235489.2991
## 2420 27138637341.7583 nan 0.0100 -21111743.6749
## 2440 27034640627.1090 nan 0.0100 -3183161.3673
## 2460 26974729543.6439 nan 0.0100 -24101730.7631
## 2480 26908141945.3167 nan 0.0100 -3199933.8393
## 2500 26826838539.2091 nan 0.0100 -11362698.3542
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 251473267149.6368 nan 0.0100 3286083333.0466
## 2 248357854177.7711 nan 0.0100 2571688701.3169
## 3 245414306418.7789 nan 0.0100 2517232266.1550
## 4 242565706290.1434 nan 0.0100 3007767369.2658
## 5 239762339990.0827 nan 0.0100 2471231877.8545
## 6 236928845309.0822 nan 0.0100 2022216073.2908
## 7 234284518584.0415 nan 0.0100 3104045997.5958
## 8 231552330412.0687 nan 0.0100 2650345092.8169
## 9 228949768020.2099 nan 0.0100 2087291439.9486
## 10 226247565826.6876 nan 0.0100 2470472925.4132
## 20 202410102004.1046 nan 0.0100 1545571680.1754
## 40 165290848110.6809 nan 0.0100 1052488751.9835
## 60 138110714320.3329 nan 0.0100 1215050482.4667
## 80 117863543682.1405 nan 0.0100 703504169.3651
## 100 102204528495.3468 nan 0.0100 648418852.2744
## 120 90124240559.0209 nan 0.0100 547961416.9950
## 140 80731109440.8547 nan 0.0100 368810077.5148
## 160 73241281872.5477 nan 0.0100 246674296.6153
## 180 67276264278.0211 nan 0.0100 212548905.3486
## 200 62163628194.0999 nan 0.0100 169882861.5903
## 220 57853819062.9788 nan 0.0100 133021280.1128
## 240 54214262398.2461 nan 0.0100 84796338.6706
## 260 51288016527.7623 nan 0.0100 107747876.9764
## 280 48773513012.6694 nan 0.0100 29685857.7960
## 300 46645375427.5889 nan 0.0100 67417059.2598
## 320 44930797148.1824 nan 0.0100 29579992.1294
## 340 43384830067.0074 nan 0.0100 19502410.4333
## 360 42083932397.8315 nan 0.0100 28226295.1669
## 380 40937790374.9119 nan 0.0100 -29704945.1914
## 400 39885182898.0826 nan 0.0100 33186982.2593
## 420 39011028876.7881 nan 0.0100 13817419.0438
## 440 38208599868.3394 nan 0.0100 34030980.0279
## 460 37500539258.6957 nan 0.0100 12189161.3099
## 480 36833319936.3298 nan 0.0100 24645852.6028
## 500 36266547693.2090 nan 0.0100 8913067.9053
## 520 35722448254.2614 nan 0.0100 12618909.3373
## 540 35216779281.4769 nan 0.0100 -14568138.0823
## 560 34721422752.0507 nan 0.0100 8712408.3663
## 580 34274491305.1489 nan 0.0100 2461516.1070
## 600 33867802702.2865 nan 0.0100 2569078.0094
## 620 33524667649.4223 nan 0.0100 7719187.5915
## 640 33175362878.6019 nan 0.0100 1163395.9124
## 660 32859141232.4425 nan 0.0100 -3139679.8514
## 680 32469836106.4234 nan 0.0100 18536415.0487
## 700 32151736622.6068 nan 0.0100 5813253.6176
## 720 31903012134.5474 nan 0.0100 -23852881.3450
## 740 31584991782.2165 nan 0.0100 26328086.7765
## 760 31303281477.0935 nan 0.0100 -35905612.3957
## 780 31035713668.1944 nan 0.0100 -41217041.6124
## 800 30782380789.9757 nan 0.0100 -4161613.9015
## 820 30521548046.3893 nan 0.0100 -10982570.6411
## 840 30279952206.3143 nan 0.0100 -11999105.7507
## 860 30023602822.7066 nan 0.0100 3623813.2774
## 880 29783042962.4242 nan 0.0100 -1749449.2646
## 900 29578137896.4253 nan 0.0100 -20919690.3660
## 920 29331209790.8699 nan 0.0100 -9744807.5658
## 940 29085965356.0578 nan 0.0100 -10376016.8530
## 960 28881772202.6377 nan 0.0100 -936390.1224
## 980 28646448518.6463 nan 0.0100 -10604508.6367
## 1000 28433001672.6122 nan 0.0100 -14758927.7095
## 1020 28272448857.7272 nan 0.0100 -670338.5424
## 1040 28091918065.6525 nan 0.0100 -11416537.6657
## 1060 27883504089.3830 nan 0.0100 -4886763.9940
## 1080 27688522781.0351 nan 0.0100 -16537728.3907
## 1100 27504263246.1557 nan 0.0100 -25038499.6966
## 1120 27340087999.4305 nan 0.0100 -8735715.8839
## 1140 27167563346.3492 nan 0.0100 -19376531.1915
## 1160 26988077322.8684 nan 0.0100 -7449882.4392
## 1180 26799063156.2918 nan 0.0100 -1834683.3420
## 1200 26615019510.6313 nan 0.0100 -8578609.7878
## 1220 26448301244.8169 nan 0.0100 -15007534.2275
## 1240 26301678030.2097 nan 0.0100 142606.7519
## 1260 26147470341.4804 nan 0.0100 -13713412.1043
## 1280 26001797040.3177 nan 0.0100 -10898034.7681
## 1300 25793814356.6005 nan 0.0100 -5228698.7775
## 1320 25650334293.2689 nan 0.0100 1806792.8222
## 1340 25517578158.5064 nan 0.0100 -13924920.5279
## 1360 25365084955.1895 nan 0.0100 -5361216.3189
## 1380 25224880814.3405 nan 0.0100 -5067376.0993
## 1400 25072802256.4151 nan 0.0100 -14215337.0164
## 1420 24915318140.4457 nan 0.0100 7960175.6646
## 1440 24752984988.4835 nan 0.0100 -3424986.8828
## 1460 24595845137.0502 nan 0.0100 -14235575.1243
## 1480 24444774196.7196 nan 0.0100 -14948174.3282
## 1500 24293807812.0591 nan 0.0100 -1164147.8279
## 1520 24158383466.6983 nan 0.0100 -3445122.0242
## 1540 24014247615.9281 nan 0.0100 -15930229.7597
## 1560 23892369386.0079 nan 0.0100 -6598454.9074
## 1580 23763952286.3698 nan 0.0100 -2515686.7544
## 1600 23632058972.6361 nan 0.0100 -8257582.9388
## 1620 23529712797.6300 nan 0.0100 -8299365.5475
## 1640 23399456863.1643 nan 0.0100 -13471212.8003
## 1660 23283666968.1996 nan 0.0100 -6226502.2135
## 1680 23154125070.9998 nan 0.0100 -4970408.3937
## 1700 23040066216.1853 nan 0.0100 622824.9973
## 1720 22933593763.1063 nan 0.0100 -5961677.7501
## 1740 22821805257.6082 nan 0.0100 -6028227.8450
## 1760 22672799706.2862 nan 0.0100 121965.5395
## 1780 22564878663.0491 nan 0.0100 -14500696.3715
## 1800 22469631146.4579 nan 0.0100 -13357896.4911
## 1820 22365612829.0138 nan 0.0100 -12618656.2142
## 1840 22249544412.2203 nan 0.0100 -20712025.1767
## 1860 22149787413.1845 nan 0.0100 -16451163.2763
## 1880 22029565565.9366 nan 0.0100 -7656746.5659
## 1900 21945963494.9984 nan 0.0100 -4226713.8547
## 1920 21821444106.4389 nan 0.0100 -89110.2911
## 1940 21731462265.4169 nan 0.0100 -2937743.2904
## 1960 21647434813.7558 nan 0.0100 -6586697.8713
## 1980 21558356937.9635 nan 0.0100 -9553077.6302
## 2000 21451774179.3482 nan 0.0100 -5554948.6594
## 2020 21349218840.0428 nan 0.0100 2306326.2928
## 2040 21267747178.3038 nan 0.0100 -2552684.3669
## 2060 21152255532.2674 nan 0.0100 -6565824.4226
## 2080 21050977698.7442 nan 0.0100 -4695614.6228
## 2100 20965848924.4041 nan 0.0100 -14862505.3629
## 2120 20888093054.8146 nan 0.0100 -2740091.7854
## 2140 20806258001.1851 nan 0.0100 -8816005.3491
## 2160 20711598022.1425 nan 0.0100 -613494.9769
## 2180 20621937642.9750 nan 0.0100 -9883247.4043
## 2200 20533362789.5260 nan 0.0100 817640.0632
## 2220 20438182390.6434 nan 0.0100 -954529.1107
## 2240 20351302059.9740 nan 0.0100 -9906298.8326
## 2260 20265754619.1280 nan 0.0100 -169380.2791
## 2280 20175824217.1605 nan 0.0100 -4811716.8159
## 2300 20090530783.8772 nan 0.0100 -1826290.2841
## 2320 20016577240.9003 nan 0.0100 -9163878.7550
## 2340 19943655366.5461 nan 0.0100 -1600765.5194
## 2360 19876284098.1621 nan 0.0100 -3607139.0631
## 2380 19809138475.7031 nan 0.0100 -496238.1395
## 2400 19743402588.4899 nan 0.0100 -4274364.7274
## 2420 19672777518.9381 nan 0.0100 -1744465.3604
## 2440 19599599192.4669 nan 0.0100 -11618685.0766
## 2460 19507512023.8750 nan 0.0100 -7502424.1117
## 2480 19424042374.3669 nan 0.0100 311781.8848
## 2500 19354346467.9957 nan 0.0100 -158453.7883
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 263649845020.3876 nan 0.0010 179433503.3919
## 2 263476432403.4903 nan 0.0010 153512697.4591
## 3 263307335929.6353 nan 0.0010 177402380.8487
## 4 263134621485.9264 nan 0.0010 139303088.3282
## 5 262970882735.7513 nan 0.0010 165063818.6461
## 6 262801769919.3634 nan 0.0010 152834878.8414
## 7 262635674833.2013 nan 0.0010 159800984.3573
## 8 262464301557.2285 nan 0.0010 153706360.6036
## 9 262301772563.0687 nan 0.0010 175855339.3947
## 10 262132990089.2972 nan 0.0010 160574865.5295
## 20 260509437585.9098 nan 0.0010 156572126.4316
## 40 257348311544.7687 nan 0.0010 155595395.6103
## 60 254278837362.2057 nan 0.0010 157137613.9457
## 80 251268310669.6859 nan 0.0010 135480457.8066
## 100 248375322087.0226 nan 0.0010 125744060.2842
## 120 245555878450.7397 nan 0.0010 133080841.8551
## 140 242869810795.7180 nan 0.0010 142234922.8979
## 160 240270313557.6025 nan 0.0010 121387182.1027
## 180 237710905563.1041 nan 0.0010 109078137.2025
## 200 235252985916.1174 nan 0.0010 113003121.6175
## 220 232855193507.9505 nan 0.0010 124285031.1416
## 240 230551678531.0745 nan 0.0010 102107885.8304
## 260 228298922727.0258 nan 0.0010 98714955.5459
## 280 226086965290.0441 nan 0.0010 107518324.1383
## 300 223973405310.8964 nan 0.0010 111402943.2041
## 320 221920448013.8396 nan 0.0010 106765897.7081
## 340 219935915175.4040 nan 0.0010 100065982.2011
## 360 217969183600.8398 nan 0.0010 84580113.3002
## 380 216080071736.3349 nan 0.0010 95556039.4857
## 400 214237073664.6391 nan 0.0010 74604719.4199
## 420 212437358893.2065 nan 0.0010 88659955.7741
## 440 210690562517.3860 nan 0.0010 73171395.5004
## 460 209000966881.7376 nan 0.0010 69782054.3641
## 480 207340915708.7516 nan 0.0010 81660316.8551
## 500 205726333250.1961 nan 0.0010 73528540.4861
## 520 204180895828.6990 nan 0.0010 69335903.9920
## 540 202656451377.6216 nan 0.0010 69759817.5039
## 560 201169085323.8999 nan 0.0010 61504976.9954
## 580 199722413315.1192 nan 0.0010 64735883.1210
## 600 198304910569.6896 nan 0.0010 72226817.2776
## 620 196905780255.8010 nan 0.0010 63400472.1509
## 640 195552852740.2477 nan 0.0010 59575083.1207
## 660 194234034518.3625 nan 0.0010 63389962.6795
## 680 192953506221.4507 nan 0.0010 51414964.3246
## 700 191711443275.4269 nan 0.0010 54692366.3683
## 720 190500132423.0033 nan 0.0010 55985483.4843
## 740 189313493156.6785 nan 0.0010 58220625.0450
## 760 188152668011.2704 nan 0.0010 58685329.7393
## 780 187005987809.0923 nan 0.0010 44042044.3157
## 800 185912378729.4778 nan 0.0010 56423575.4637
## 820 184801356848.6253 nan 0.0010 49678868.4021
## 840 183707864973.1760 nan 0.0010 49162796.7036
## 860 182645851196.3645 nan 0.0010 55438805.4164
## 880 181602161085.1898 nan 0.0010 33379090.1672
## 900 180579266622.1680 nan 0.0010 31826666.4186
## 920 179563431289.4457 nan 0.0010 44449608.9895
## 940 178559255204.5368 nan 0.0010 47054584.9537
## 960 177586363390.3557 nan 0.0010 39138802.7159
## 980 176624858941.3067 nan 0.0010 48372127.7348
## 1000 175661255985.3788 nan 0.0010 33363864.9880
## 1020 174718456058.1212 nan 0.0010 30655780.1680
## 1040 173792106258.1647 nan 0.0010 44216141.0727
## 1060 172893514516.6281 nan 0.0010 33578544.1454
## 1080 171979372797.8124 nan 0.0010 35921169.0036
## 1100 171094038450.6944 nan 0.0010 34358076.1731
## 1120 170218116214.2184 nan 0.0010 28365074.3657
## 1140 169364358435.5181 nan 0.0010 38711869.6499
## 1160 168526743263.0847 nan 0.0010 43347302.5014
## 1180 167704540633.2660 nan 0.0010 29907492.7324
## 1200 166871035769.4257 nan 0.0010 32843635.5812
## 1220 166049811357.5835 nan 0.0010 32021341.2372
## 1240 165252171676.4847 nan 0.0010 40481129.5767
## 1260 164454060217.0748 nan 0.0010 25956939.3298
## 1280 163670016167.5786 nan 0.0010 30386575.0101
## 1300 162892665858.4168 nan 0.0010 38923625.8931
## 1320 162124928259.6165 nan 0.0010 36015476.1894
## 1340 161386112386.8211 nan 0.0010 38893244.8499
## 1360 160645204322.8777 nan 0.0010 38556833.9460
## 1380 159916595885.8610 nan 0.0010 36342723.0267
## 1400 159198231914.5093 nan 0.0010 31850992.7676
## 1420 158483405578.5013 nan 0.0010 33672587.0829
## 1440 157782591181.4909 nan 0.0010 24608807.8463
## 1460 157102937659.7911 nan 0.0010 32333241.5990
## 1480 156424586011.7252 nan 0.0010 28223108.3042
## 1500 155759080674.1826 nan 0.0010 33535333.2133
## 1520 155081337271.2288 nan 0.0010 30856967.1879
## 1540 154421420037.6374 nan 0.0010 27393371.8870
## 1560 153771928757.2958 nan 0.0010 20021261.8614
## 1580 153122281519.9857 nan 0.0010 23828356.9710
## 1600 152474445876.2222 nan 0.0010 23487184.2296
## 1620 151847557763.2202 nan 0.0010 33267847.3145
## 1640 151217495697.9921 nan 0.0010 31895010.5380
## 1660 150603274959.8442 nan 0.0010 21297830.2376
## 1680 149995877429.7393 nan 0.0010 24480150.8304
## 1700 149395720834.3163 nan 0.0010 20946223.8402
## 1720 148805216066.0499 nan 0.0010 24344815.4669
## 1740 148225773736.9110 nan 0.0010 29363112.3205
## 1760 147644977235.8097 nan 0.0010 30852703.8186
## 1780 147076742864.8329 nan 0.0010 14025189.5305
## 1800 146511109542.9213 nan 0.0010 25266268.1110
## 1820 145959167942.5119 nan 0.0010 12758825.4392
## 1840 145408732052.0284 nan 0.0010 29450741.4322
## 1860 144861467182.3249 nan 0.0010 16913767.8770
## 1880 144312103925.7632 nan 0.0010 16353478.4660
## 1900 143776291802.3963 nan 0.0010 13016126.2095
## 1920 143242285160.2819 nan 0.0010 27323822.7451
## 1940 142716360162.7063 nan 0.0010 15156415.3026
## 1960 142197394530.5377 nan 0.0010 26555857.3183
## 1980 141679573692.9731 nan 0.0010 21736214.2041
## 2000 141169470128.3562 nan 0.0010 21604474.1332
## 2020 140670156219.7327 nan 0.0010 12608772.7170
## 2040 140172350680.0389 nan 0.0010 19373006.5042
## 2060 139688541574.5679 nan 0.0010 23209435.1653
## 2080 139196282648.9810 nan 0.0010 11552516.9031
## 2100 138727090784.7448 nan 0.0010 23420313.5490
## 2120 138252912866.9327 nan 0.0010 15809015.7129
## 2140 137791348718.2758 nan 0.0010 6318334.1607
## 2160 137332255565.3172 nan 0.0010 19270757.7551
## 2180 136868943692.1266 nan 0.0010 14412661.0690
## 2200 136418426485.4331 nan 0.0010 17625553.3471
## 2220 135970309754.6348 nan 0.0010 14156722.1796
## 2240 135528983163.7096 nan 0.0010 9601856.3181
## 2260 135095065049.7591 nan 0.0010 11379634.2423
## 2280 134663337383.5459 nan 0.0010 22605506.1623
## 2300 134246971963.9526 nan 0.0010 15735266.7567
## 2320 133836517203.2605 nan 0.0010 5692452.3794
## 2340 133421539805.9309 nan 0.0010 6442020.5772
## 2360 133005752260.7387 nan 0.0010 19750956.2364
## 2380 132597214188.1533 nan 0.0010 10746152.5796
## 2400 132189617995.6867 nan 0.0010 5765912.6573
## 2420 131789449153.6129 nan 0.0010 19651691.5104
## 2440 131393460315.1827 nan 0.0010 6023947.6748
## 2460 131003841599.1666 nan 0.0010 13816748.9183
## 2480 130620363188.9987 nan 0.0010 15069818.7849
## 2500 130235454865.1699 nan 0.0010 17485423.1773
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 263538234137.1451 nan 0.0010 241511806.1909
## 2 263250805725.7722 nan 0.0010 246073555.2168
## 3 262989664736.4086 nan 0.0010 263408989.4946
## 4 262717724839.5914 nan 0.0010 270040174.3898
## 5 262439274362.6504 nan 0.0010 256940534.0272
## 6 262172371384.2660 nan 0.0010 250326351.4134
## 7 261886635259.3316 nan 0.0010 233844614.0736
## 8 261615695302.1745 nan 0.0010 245937523.9710
## 9 261342760015.4219 nan 0.0010 268078621.6219
## 10 261063757797.6653 nan 0.0010 303780585.4010
## 20 258460784600.8508 nan 0.0010 296082205.6230
## 40 253304503323.7339 nan 0.0010 224053788.3107
## 60 248246581667.1246 nan 0.0010 188063380.9542
## 80 243428703077.1796 nan 0.0010 229399505.6442
## 100 238741071564.0253 nan 0.0010 227433828.7608
## 120 234174510022.0653 nan 0.0010 241532473.9120
## 140 229803171477.6568 nan 0.0010 153218284.8884
## 160 225588719455.2951 nan 0.0010 199000147.3648
## 180 221490838631.5230 nan 0.0010 174553786.5432
## 200 217545435576.0412 nan 0.0010 184597015.0412
## 220 213660931793.0732 nan 0.0010 173745893.6144
## 240 209925448532.6703 nan 0.0010 164526012.6717
## 260 206317740316.4323 nan 0.0010 147433716.2965
## 280 202822972345.8406 nan 0.0010 131107133.3396
## 300 199462052812.4533 nan 0.0010 118574344.7540
## 320 196210784069.8076 nan 0.0010 128067020.6674
## 340 193037240542.3769 nan 0.0010 152361340.5233
## 360 189946702159.9584 nan 0.0010 111907037.1131
## 380 187008681281.6026 nan 0.0010 128970843.3090
## 400 184101106258.9028 nan 0.0010 91732678.0605
## 420 181313166341.1376 nan 0.0010 121107682.8648
## 440 178638339632.4970 nan 0.0010 137494649.9038
## 460 176012634132.4550 nan 0.0010 99709616.1137
## 480 173434111697.6165 nan 0.0010 86493691.2861
## 500 170937416199.2106 nan 0.0010 124848563.1788
## 520 168510324813.8306 nan 0.0010 113229254.7995
## 540 166152331138.4653 nan 0.0010 110018772.3836
## 560 163846483354.7226 nan 0.0010 81733838.2744
## 580 161666678239.0908 nan 0.0010 107319091.3927
## 600 159517560387.7064 nan 0.0010 106401353.8032
## 620 157428454843.3760 nan 0.0010 84316032.3473
## 640 155417726837.8017 nan 0.0010 56965127.3262
## 660 153396318324.8957 nan 0.0010 79293743.6120
## 680 151443323814.2061 nan 0.0010 96892797.5570
## 700 149505992642.2293 nan 0.0010 81378579.1176
## 720 147682642095.0911 nan 0.0010 82059954.5326
## 740 145865224936.1456 nan 0.0010 94127784.7046
## 760 144094357298.3562 nan 0.0010 103266152.6056
## 780 142353464770.3116 nan 0.0010 90782243.8651
## 800 140678703357.3055 nan 0.0010 85197245.2968
## 820 139035731908.6835 nan 0.0010 54979657.3964
## 840 137407645434.8575 nan 0.0010 65143382.2837
## 860 135841009235.0140 nan 0.0010 71699099.1861
## 880 134285502945.4795 nan 0.0010 65033024.5998
## 900 132788802173.7664 nan 0.0010 65697141.8725
## 920 131292100869.4451 nan 0.0010 59186730.7746
## 940 129840545793.0734 nan 0.0010 67573806.0332
## 960 128424420705.5001 nan 0.0010 76592453.8927
## 980 127023566919.8641 nan 0.0010 65152959.3972
## 1000 125700841574.1379 nan 0.0010 58315433.8798
## 1020 124407992477.4880 nan 0.0010 48104095.3932
## 1040 123092551221.6066 nan 0.0010 55932978.2061
## 1060 121839093341.2241 nan 0.0010 34252237.7706
## 1080 120596198906.0603 nan 0.0010 61412994.3593
## 1100 119375943720.2882 nan 0.0010 61413438.7809
## 1120 118195575165.1868 nan 0.0010 51340197.3149
## 1140 117057531647.7800 nan 0.0010 50770370.2061
## 1160 115918716889.5890 nan 0.0010 40931653.6936
## 1180 114797341507.0496 nan 0.0010 53540052.0033
## 1200 113710580864.6024 nan 0.0010 51419041.0348
## 1220 112652009757.4730 nan 0.0010 42073558.1057
## 1240 111597749762.6624 nan 0.0010 37594417.5719
## 1260 110571047552.9504 nan 0.0010 51820095.4650
## 1280 109575380023.1268 nan 0.0010 44126129.6450
## 1300 108600915584.0622 nan 0.0010 49300236.3938
## 1320 107643827402.2208 nan 0.0010 26356659.2561
## 1340 106684857475.5855 nan 0.0010 16230392.9520
## 1360 105746861524.1609 nan 0.0010 30972592.9018
## 1380 104847087706.3447 nan 0.0010 32115594.3631
## 1400 103961818648.3388 nan 0.0010 40546756.1199
## 1420 103091882327.7216 nan 0.0010 33450373.6967
## 1440 102207793780.4942 nan 0.0010 41972277.6807
## 1460 101326340459.6916 nan 0.0010 14056667.5722
## 1480 100493537941.3037 nan 0.0010 19245554.3002
## 1500 99648658797.7072 nan 0.0010 34484972.7073
## 1520 98858998239.8384 nan 0.0010 36398654.5229
## 1540 98069846137.1776 nan 0.0010 23870205.4402
## 1560 97295172576.5743 nan 0.0010 50035368.5405
## 1580 96530186135.8629 nan 0.0010 9002537.6192
## 1600 95799706555.6131 nan 0.0010 34276449.7087
## 1620 95064850372.7729 nan 0.0010 32410558.4590
## 1640 94325618126.9219 nan 0.0010 35747548.6382
## 1660 93612269438.4216 nan 0.0010 27368260.1248
## 1680 92917771340.2423 nan 0.0010 24082895.0723
## 1700 92217268135.9457 nan 0.0010 54988698.7113
## 1720 91522116648.3377 nan 0.0010 32852937.6723
## 1740 90862780050.3306 nan 0.0010 19400000.8222
## 1760 90203131268.8621 nan 0.0010 11429437.6761
## 1780 89568206429.3463 nan 0.0010 12569853.7762
## 1800 88919475398.1725 nan 0.0010 29591176.0764
## 1820 88286365682.5150 nan 0.0010 19909333.7905
## 1840 87674013994.9705 nan 0.0010 16912705.5929
## 1860 87059151925.5768 nan 0.0010 40660441.7811
## 1880 86450399126.7792 nan 0.0010 29913271.7500
## 1900 85848209691.8520 nan 0.0010 36965823.4641
## 1920 85240650709.2588 nan 0.0010 22619431.5225
## 1940 84671553197.2142 nan 0.0010 16622861.3908
## 1960 84084877417.6752 nan 0.0010 21154413.9752
## 1980 83531164239.9053 nan 0.0010 26235347.6203
## 2000 82979597160.8842 nan 0.0010 34169277.0823
## 2020 82438448257.6223 nan 0.0010 18851441.5096
## 2040 81883044571.0626 nan 0.0010 21440648.1453
## 2060 81336097327.9878 nan 0.0010 22847797.2866
## 2080 80813211470.0544 nan 0.0010 13855120.0804
## 2100 80286883261.7285 nan 0.0010 24644438.1177
## 2120 79769944183.4330 nan 0.0010 28104944.9605
## 2140 79272078546.9360 nan 0.0010 11796300.8946
## 2160 78767126664.7528 nan 0.0010 21384357.8134
## 2180 78245791208.6240 nan 0.0010 17795708.0287
## 2200 77754089285.2719 nan 0.0010 32670335.8244
## 2220 77272340311.1592 nan 0.0010 20640627.0954
## 2240 76789797286.0311 nan 0.0010 21627940.6475
## 2260 76330648203.3431 nan 0.0010 21800878.3710
## 2280 75847225461.9305 nan 0.0010 16607181.8791
## 2300 75399807470.0229 nan 0.0010 14064228.1579
## 2320 74949822339.7223 nan 0.0010 17718492.0297
## 2340 74517270362.5341 nan 0.0010 14993733.1885
## 2360 74085749233.7927 nan 0.0010 23486843.4284
## 2380 73647463613.4729 nan 0.0010 26228373.3715
## 2400 73228429100.5531 nan 0.0010 17392086.8517
## 2420 72801643758.1476 nan 0.0010 5021317.7396
## 2440 72387639075.3969 nan 0.0010 632699.1000
## 2460 71987999692.9923 nan 0.0010 13314692.7571
## 2480 71582246373.3562 nan 0.0010 19429499.4578
## 2500 71210068361.1002 nan 0.0010 11168984.4521
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 263505468935.7038 nan 0.0010 305202695.5493
## 2 263184146974.3650 nan 0.0010 327265526.7271
## 3 262872570578.7297 nan 0.0010 358011976.8177
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## 6 261946737815.6639 nan 0.0010 293915851.9121
## 7 261620665055.3247 nan 0.0010 267888150.0635
## 8 261294068378.9666 nan 0.0010 233967920.0258
## 9 260986651225.9935 nan 0.0010 279092909.1825
## 10 260664045215.7155 nan 0.0010 250913803.8370
## 20 257605955252.6446 nan 0.0010 348767707.6927
## 40 251581751778.4452 nan 0.0010 244108734.2308
## 60 245851249897.2135 nan 0.0010 277911999.3129
## 80 240271465871.7105 nan 0.0010 272002245.7263
## 100 234917599553.8760 nan 0.0010 240850942.8730
## 120 229696946993.7315 nan 0.0010 253562549.9345
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## 160 219883636111.6178 nan 0.0010 203971817.1744
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## 240 202105755337.5180 nan 0.0010 192112666.2666
## 260 197997809260.1301 nan 0.0010 206155739.9235
## 280 194046536828.6014 nan 0.0010 203019412.5129
## 300 190222804504.8689 nan 0.0010 147404020.3845
## 320 186547916513.6474 nan 0.0010 191143224.3052
## 340 182946082562.3953 nan 0.0010 209824253.8548
## 360 179473925338.8383 nan 0.0010 163143392.6027
## 380 176138377154.1282 nan 0.0010 170111000.2516
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## 560 150031824645.7908 nan 0.0010 92721950.4777
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## 600 145085812813.4355 nan 0.0010 81634066.7154
## 620 142692510720.0022 nan 0.0010 125765899.3711
## 640 140432515737.2215 nan 0.0010 100915000.2122
## 660 138243678491.9432 nan 0.0010 109985612.1210
## 680 136100932462.4475 nan 0.0010 115474120.0509
## 700 134011655040.7477 nan 0.0010 80175009.8117
## 720 131987719154.7033 nan 0.0010 102609417.3183
## 740 130015011889.4166 nan 0.0010 80474531.0337
## 760 128104909695.0589 nan 0.0010 100775006.8704
## 780 126224490371.8977 nan 0.0010 88324513.2627
## 800 124437101245.6247 nan 0.0010 55819373.9919
## 820 122657239154.4046 nan 0.0010 71947345.3297
## 840 120948017467.8949 nan 0.0010 83778471.8817
## 860 119240041323.0630 nan 0.0010 59655435.0172
## 880 117609739907.7625 nan 0.0010 92880701.8063
## 900 116008422008.9823 nan 0.0010 67298611.9846
## 920 114443670327.1333 nan 0.0010 79712503.0982
## 940 112923305649.9283 nan 0.0010 73315784.1858
## 960 111450215887.7607 nan 0.0010 31970894.3571
## 980 110015499857.8989 nan 0.0010 53734839.3535
## 1000 108599420893.2951 nan 0.0010 58472544.2996
## 1020 107218537612.6666 nan 0.0010 43330488.9873
## 1040 105882730485.9584 nan 0.0010 61205030.9301
## 1060 104552088486.6818 nan 0.0010 38890387.5266
## 1080 103278155751.0831 nan 0.0010 59708315.9788
## 1100 102031128079.8047 nan 0.0010 47858337.6600
## 1120 100820814179.6064 nan 0.0010 32317646.9606
## 1140 99642691255.4055 nan 0.0010 50010508.4902
## 1160 98502295978.1753 nan 0.0010 42136123.7184
## 1180 97377875899.6810 nan 0.0010 53816819.3458
## 1200 96264844472.1629 nan 0.0010 58907695.0643
## 1220 95155611846.8263 nan 0.0010 42859759.2200
## 1240 94094540493.4587 nan 0.0010 57143252.1861
## 1260 93030352089.7193 nan 0.0010 37005030.0703
## 1280 92022253490.3495 nan 0.0010 38480418.7885
## 1300 91029239944.4460 nan 0.0010 48064319.6855
## 1320 90075310866.7627 nan 0.0010 34167141.3226
## 1340 89123846101.3632 nan 0.0010 45461330.5318
## 1360 88195868941.5917 nan 0.0010 38374085.0779
## 1380 87295465730.3002 nan 0.0010 40998614.9953
## 1400 86390707117.0302 nan 0.0010 40898365.7892
## 1420 85514452022.1259 nan 0.0010 39152796.7823
## 1440 84671780178.5437 nan 0.0010 29245801.9435
## 1460 83831092951.2129 nan 0.0010 34997610.8327
## 1480 83026798451.6559 nan 0.0010 28732536.5381
## 1500 82226339617.7799 nan 0.0010 31833912.4680
## 1520 81452105283.5783 nan 0.0010 36529706.0096
## 1540 80685740778.6913 nan 0.0010 27249270.9116
## 1560 79921758993.9899 nan 0.0010 40234457.8780
## 1580 79185661868.4973 nan 0.0010 33334357.2594
## 1600 78456841355.8658 nan 0.0010 17286027.3016
## 1620 77736827794.4776 nan 0.0010 26540711.4321
## 1640 77032629543.5738 nan 0.0010 20772630.2291
## 1660 76348542209.3943 nan 0.0010 32696897.7381
## 1680 75684981526.9200 nan 0.0010 27679206.1323
## 1700 75031370928.6689 nan 0.0010 20301725.8594
## 1720 74378986310.7968 nan 0.0010 24298135.9682
## 1740 73736052132.6449 nan 0.0010 20197518.3414
## 1760 73123162827.4454 nan 0.0010 25231530.5470
## 1780 72515677672.9367 nan 0.0010 14417677.4057
## 1800 71907148749.9817 nan 0.0010 10897105.1111
## 1820 71321474254.8873 nan 0.0010 28554081.2233
## 1840 70746358683.1476 nan 0.0010 17344910.4556
## 1860 70179518155.6010 nan 0.0010 19043246.6949
## 1880 69614659218.8962 nan 0.0010 19493447.1965
## 1900 69081169913.7207 nan 0.0010 16561114.9068
## 1920 68537393007.7080 nan 0.0010 14763769.7926
## 1940 67992411037.2064 nan 0.0010 28245072.1995
## 1960 67467957094.5942 nan 0.0010 22627797.5340
## 1980 66964636772.6078 nan 0.0010 9081939.8662
## 2000 66472829971.7954 nan 0.0010 16862687.8569
## 2020 65991418764.4800 nan 0.0010 19641370.8965
## 2040 65519660492.1387 nan 0.0010 11212194.8502
## 2060 65056575007.9647 nan 0.0010 14891113.9065
## 2080 64583962436.9711 nan 0.0010 27106702.4064
## 2100 64108557084.4027 nan 0.0010 9979020.1716
## 2120 63642987050.7369 nan 0.0010 23959523.1758
## 2140 63195300647.6870 nan 0.0010 9226726.7214
## 2160 62765401592.4057 nan 0.0010 10148968.6930
## 2180 62339303140.7674 nan 0.0010 15878967.2982
## 2200 61916117469.9309 nan 0.0010 13892421.2192
## 2220 61500283509.0275 nan 0.0010 17943999.4080
## 2240 61081910969.2241 nan 0.0010 24347232.7377
## 2260 60670101176.7799 nan 0.0010 19382043.1142
## 2280 60281098191.7311 nan 0.0010 11698428.1908
## 2300 59894352463.3244 nan 0.0010 16785591.0456
## 2320 59517848369.4109 nan 0.0010 13184378.0794
## 2340 59154070406.6745 nan 0.0010 19031962.7882
## 2360 58792622026.5640 nan 0.0010 15272831.1826
## 2380 58437278661.3612 nan 0.0010 12441971.2127
## 2400 58085363553.1041 nan 0.0010 7826787.5958
## 2420 57744983919.1015 nan 0.0010 10167801.6146
## 2440 57411925953.0934 nan 0.0010 20426267.9808
## 2460 57087714839.4330 nan 0.0010 3900351.2923
## 2480 56763251251.6994 nan 0.0010 11810461.3026
## 2500 56436675308.6547 nan 0.0010 6891813.4995
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 262230233525.3368 nan 0.0100 1756702111.5083
## 2 260506560488.0608 nan 0.0100 1424642625.1435
## 3 258968447361.8160 nan 0.0100 1863741808.1057
## 4 257360154229.4964 nan 0.0100 1548776525.6267
## 5 255764698015.4959 nan 0.0100 1491183912.4791
## 6 254275845773.5856 nan 0.0100 1592244879.4836
## 7 252766931154.6319 nan 0.0100 1409655869.2741
## 8 251277857142.8353 nan 0.0100 1411391820.6696
## 9 249791036560.0368 nan 0.0100 1292105770.0742
## 10 248384374160.3102 nan 0.0100 1493668449.4857
## 20 235176690205.9695 nan 0.0100 1199257855.8512
## 40 214036958501.3496 nan 0.0100 678877986.9152
## 60 198070655950.6290 nan 0.0100 667624228.1280
## 80 185638125433.4874 nan 0.0100 430112471.5874
## 100 175467148655.9474 nan 0.0100 457784950.8088
## 120 166717656665.0028 nan 0.0100 398874422.3531
## 140 159111241827.9881 nan 0.0100 336940786.9147
## 160 152276855002.7588 nan 0.0100 163825618.4166
## 180 146289947131.5670 nan 0.0100 251348939.0209
## 200 140971476505.1280 nan 0.0100 224887456.6967
## 220 136209414068.6716 nan 0.0100 181492159.7624
## 240 132035015624.2209 nan 0.0100 168141940.1542
## 260 128257623931.1863 nan 0.0100 168816703.6591
## 280 124821630492.2439 nan 0.0100 168381766.6826
## 300 121641783527.7670 nan 0.0100 29769775.8240
## 320 118757138883.7165 nan 0.0100 138294509.2091
## 340 116105096136.4138 nan 0.0100 121309992.6036
## 360 113680254138.0673 nan 0.0100 100131583.0437
## 380 111454334642.5650 nan 0.0100 104875079.1032
## 400 109383886186.1072 nan 0.0100 102685558.6417
## 420 107489890927.3352 nan 0.0100 79667599.2735
## 440 105686965072.4949 nan 0.0100 56223180.7764
## 460 104006525764.6017 nan 0.0100 78881000.5742
## 480 102455010468.0226 nan 0.0100 14733420.5849
## 500 101020110851.1561 nan 0.0100 60114194.9322
## 520 99656645528.1481 nan 0.0100 62877183.5664
## 540 98400451833.7018 nan 0.0100 60624220.6394
## 560 97208686003.5406 nan 0.0100 48672944.7612
## 580 96124890951.4723 nan 0.0100 31742338.8361
## 600 95108093671.9753 nan 0.0100 21522211.7748
## 620 94167576053.5200 nan 0.0100 47234651.8645
## 640 93275643701.1195 nan 0.0100 45450507.6531
## 660 92419714879.2465 nan 0.0100 34828748.9341
## 680 91636221704.9434 nan 0.0100 39577851.4118
## 700 90886824150.1475 nan 0.0100 -4190240.7645
## 720 90189279887.1721 nan 0.0100 281653.2568
## 740 89538162830.6861 nan 0.0100 29864400.3287
## 760 88922826282.1996 nan 0.0100 13109602.0512
## 780 88325643247.9824 nan 0.0100 26948137.9930
## 800 87775329518.1280 nan 0.0100 -10837767.7077
## 820 87261301147.1012 nan 0.0100 -29061276.2349
## 840 86779229870.7088 nan 0.0100 24034342.4355
## 860 86299130395.6644 nan 0.0100 -48268710.7677
## 880 85863660124.5237 nan 0.0100 17377143.0634
## 900 85449032122.2900 nan 0.0100 6347639.4466
## 920 85042687711.7594 nan 0.0100 9613727.3525
## 940 84684913186.5122 nan 0.0100 13804048.1120
## 960 84330622466.7585 nan 0.0100 16755749.5679
## 980 84015901945.7947 nan 0.0100 9063524.9629
## 1000 83703182820.9910 nan 0.0100 -3192838.1465
## 1020 83398573698.4307 nan 0.0100 5391853.2412
## 1040 83116940526.9687 nan 0.0100 11807724.0418
## 1060 82840383357.4628 nan 0.0100 -7049950.4251
## 1080 82605444369.0393 nan 0.0100 -46914585.6884
## 1100 82355215468.0236 nan 0.0100 12291380.7784
## 1120 82122855002.9559 nan 0.0100 8778440.1889
## 1140 81908758906.8172 nan 0.0100 8784947.6022
## 1160 81701146689.7068 nan 0.0100 7422748.9695
## 1180 81485213392.2239 nan 0.0100 11400715.6078
## 1200 81279278004.8910 nan 0.0100 6953534.4795
## 1220 81085806877.8466 nan 0.0100 6313548.3475
## 1240 80908044268.3402 nan 0.0100 6186387.1291
## 1260 80740494191.8690 nan 0.0100 -13358508.4059
## 1280 80551932477.0860 nan 0.0100 7555279.1996
## 1300 80376562350.7915 nan 0.0100 -5560648.7314
## 1320 80221303782.6670 nan 0.0100 -19043034.0091
## 1340 80062768213.1804 nan 0.0100 6123634.3241
## 1360 79921227919.5410 nan 0.0100 -15876372.8121
## 1380 79778930654.9712 nan 0.0100 -26120265.5727
## 1400 79649149530.9948 nan 0.0100 1546592.0845
## 1420 79503079973.0715 nan 0.0100 -51775.9278
## 1440 79376566876.5062 nan 0.0100 4449146.1018
## 1460 79244971408.2151 nan 0.0100 -12833682.6420
## 1480 79114778695.6103 nan 0.0100 -6389974.6041
## 1500 78989861437.9580 nan 0.0100 -25257084.5741
## 1520 78883535416.1427 nan 0.0100 -35874087.4506
## 1540 78776986402.5240 nan 0.0100 -29244478.6734
## 1560 78662530418.0749 nan 0.0100 4868009.0135
## 1580 78555680021.5906 nan 0.0100 -7628898.3644
## 1600 78448046230.2613 nan 0.0100 2470993.0720
## 1620 78359562217.8094 nan 0.0100 -28388646.4678
## 1640 78245408610.7262 nan 0.0100 -25181484.6094
## 1660 78129440176.4389 nan 0.0100 -19806251.0592
## 1680 78031664494.9906 nan 0.0100 4010546.9532
## 1700 77946809991.0450 nan 0.0100 -31332270.7736
## 1720 77850680296.3216 nan 0.0100 3379177.0697
## 1740 77767068359.5726 nan 0.0100 -239271.9309
## 1760 77679607228.1957 nan 0.0100 -10713716.6696
## 1780 77594569179.5464 nan 0.0100 -15157849.7064
## 1800 77508363685.8047 nan 0.0100 2811562.4239
## 1820 77419579805.0634 nan 0.0100 -21217246.8425
## 1840 77346096211.7601 nan 0.0100 -13765438.7447
## 1860 77275924343.1214 nan 0.0100 -8204041.7546
## 1880 77195900788.0067 nan 0.0100 -12582387.8328
## 1900 77122028162.8992 nan 0.0100 -16582440.9557
## 1920 77040002102.7162 nan 0.0100 -8325523.6368
## 1940 76973536131.0893 nan 0.0100 -17320888.6434
## 1960 76899428918.6396 nan 0.0100 1328783.8147
## 1980 76831404649.5071 nan 0.0100 -14788551.7036
## 2000 76774751560.1616 nan 0.0100 -26271155.8682
## 2020 76707571739.4349 nan 0.0100 1998355.4826
## 2040 76636568506.4629 nan 0.0100 -14521313.1291
## 2060 76572587183.1122 nan 0.0100 -5926893.9153
## 2080 76506186911.4781 nan 0.0100 -8299607.6687
## 2100 76437602978.8490 nan 0.0100 -7869332.0835
## 2120 76368319230.8729 nan 0.0100 2862745.1235
## 2140 76298213130.1378 nan 0.0100 -30238708.0393
## 2160 76243824719.4859 nan 0.0100 -10128554.6406
## 2180 76196350057.4469 nan 0.0100 2263607.3981
## 2200 76136857407.8288 nan 0.0100 -44091625.8312
## 2220 76074296878.4082 nan 0.0100 1616967.3249
## 2240 76009440783.6797 nan 0.0100 -18108454.0687
## 2260 75944646540.2370 nan 0.0100 -1100851.3164
## 2280 75880460261.0380 nan 0.0100 -10711046.2199
## 2300 75818921442.6018 nan 0.0100 427728.6335
## 2320 75758823333.7843 nan 0.0100 -9969714.9532
## 2340 75709081109.4497 nan 0.0100 -14181499.0166
## 2360 75652000745.7061 nan 0.0100 -23231407.7199
## 2380 75597668869.3975 nan 0.0100 -12525069.5778
## 2400 75552056026.2648 nan 0.0100 912738.1050
## 2420 75501840270.5956 nan 0.0100 2657698.0841
## 2440 75451545263.6087 nan 0.0100 1383492.2598
## 2460 75401973966.5312 nan 0.0100 -13410155.5659
## 2480 75357212650.7831 nan 0.0100 -9562390.3091
## 2500 75302862902.2231 nan 0.0100 -20014547.4034
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 260933664230.9712 nan 0.0100 2535509276.5355
## 2 258435470634.8389 nan 0.0100 2635546603.7388
## 3 255730856626.3704 nan 0.0100 2664579254.0434
## 4 253061379920.1119 nan 0.0100 2068878364.2095
## 5 250501547294.0819 nan 0.0100 2029756932.2169
## 6 248036312276.0443 nan 0.0100 2442652817.2425
## 7 245638119416.1932 nan 0.0100 2717567301.0873
## 8 243329319775.4806 nan 0.0100 2297927873.6688
## 9 240919467353.0830 nan 0.0100 2120870515.4268
## 10 238485210463.4436 nan 0.0100 2364438390.2886
## 20 217233465652.5146 nan 0.0100 1518341338.2036
## 40 183722728656.1247 nan 0.0100 1698131457.5426
## 60 159079601324.6606 nan 0.0100 990702077.1239
## 80 140442991083.8636 nan 0.0100 855335050.6781
## 100 125361017958.8251 nan 0.0100 690507104.5278
## 120 113151659810.7635 nan 0.0100 520115083.1471
## 140 103647396562.6944 nan 0.0100 358965849.8786
## 160 95577875812.1475 nan 0.0100 297646178.4453
## 180 88854460991.2127 nan 0.0100 329910839.6197
## 200 83004249957.8970 nan 0.0100 230600525.6026
## 220 77896169803.4025 nan 0.0100 174433913.2738
## 240 73360015258.9597 nan 0.0100 218463787.6843
## 260 69516861900.5178 nan 0.0100 35616828.9038
## 280 66173242686.5045 nan 0.0100 61440506.1855
## 300 63205799824.4433 nan 0.0100 44657085.2777
## 320 60577698267.3906 nan 0.0100 94736978.4641
## 340 58338701121.1847 nan 0.0100 -51976917.9945
## 360 56344447780.7875 nan 0.0100 80245949.4269
## 380 54591747007.6887 nan 0.0100 48219907.3787
## 400 53056943223.6876 nan 0.0100 71865204.7418
## 420 51771744504.3714 nan 0.0100 11533020.3252
## 440 50618504772.5450 nan 0.0100 56519063.4892
## 460 49591492563.4236 nan 0.0100 17938558.0029
## 480 48714266171.9088 nan 0.0100 9869173.9904
## 500 47863047031.7875 nan 0.0100 35332305.6470
## 520 47115560858.2860 nan 0.0100 -34936116.2807
## 540 46413110227.8693 nan 0.0100 -13702498.3999
## 560 45758680068.5386 nan 0.0100 30292870.1370
## 580 45190634430.3571 nan 0.0100 18131457.5564
## 600 44684205705.0247 nan 0.0100 37237605.2291
## 620 44195431324.3624 nan 0.0100 -4767571.2657
## 640 43708078233.2210 nan 0.0100 13728670.5232
## 660 43286048260.8441 nan 0.0100 11958237.2951
## 680 42916363515.5845 nan 0.0100 -21455332.8819
## 700 42556358563.1377 nan 0.0100 -13866803.2388
## 720 42190936036.9906 nan 0.0100 -3177846.6714
## 740 41833812720.4427 nan 0.0100 196301.5033
## 760 41478132759.0274 nan 0.0100 -4107098.9856
## 780 41173624077.4739 nan 0.0100 10783979.6285
## 800 40852287117.1362 nan 0.0100 3741569.6223
## 820 40526718292.5219 nan 0.0100 8574432.2121
## 840 40264907420.1430 nan 0.0100 -19722865.7353
## 860 40009760786.7783 nan 0.0100 2191096.8214
## 880 39752207319.5180 nan 0.0100 7327598.9863
## 900 39498974760.5383 nan 0.0100 -17641097.8405
## 920 39266287044.0455 nan 0.0100 -7958137.6436
## 940 39049200965.6181 nan 0.0100 -69759291.5694
## 960 38822274103.7801 nan 0.0100 5981068.4550
## 980 38581765766.8383 nan 0.0100 -4279232.1064
## 1000 38331961571.9924 nan 0.0100 2296425.5615
## 1020 38047583578.5673 nan 0.0100 -29924360.4597
## 1040 37808712212.7749 nan 0.0100 -8406238.1776
## 1060 37613748720.1771 nan 0.0100 -14509404.9922
## 1080 37374071804.9456 nan 0.0100 4374030.8337
## 1100 37184740041.0162 nan 0.0100 -17204993.3199
## 1120 36936643004.9248 nan 0.0100 -11336993.1065
## 1140 36740991965.4721 nan 0.0100 -18900711.6985
## 1160 36523119608.2940 nan 0.0100 3063309.9753
## 1180 36338123683.8150 nan 0.0100 -4295417.4198
## 1200 36140425227.5929 nan 0.0100 -15857166.1041
## 1220 35989390921.1673 nan 0.0100 -118088.4368
## 1240 35794785774.9620 nan 0.0100 -3698886.3047
## 1260 35603542669.9560 nan 0.0100 -29637867.9797
## 1280 35434603967.8180 nan 0.0100 -3180159.5807
## 1300 35216479195.1950 nan 0.0100 -6616372.0758
## 1320 35046255982.0219 nan 0.0100 625622.2441
## 1340 34883748527.0632 nan 0.0100 -1768227.0423
## 1360 34740244917.9646 nan 0.0100 2277696.6139
## 1380 34563059179.6603 nan 0.0100 -3977909.4891
## 1400 34416837842.4609 nan 0.0100 -6909385.0713
## 1420 34284858798.7060 nan 0.0100 -3006452.2339
## 1440 34115917449.6264 nan 0.0100 -11534979.3245
## 1460 33971142712.2970 nan 0.0100 -9955148.1463
## 1480 33859547272.6855 nan 0.0100 -9665182.3090
## 1500 33729475130.7114 nan 0.0100 -8932378.9694
## 1520 33568063781.6623 nan 0.0100 -2320288.7806
## 1540 33429632414.1912 nan 0.0100 -16222754.5554
## 1560 33291560601.3274 nan 0.0100 -1373733.7804
## 1580 33182384609.5505 nan 0.0100 -3818941.5590
## 1600 33060841956.1308 nan 0.0100 1861882.0177
## 1620 32914809486.6058 nan 0.0100 -7789554.1804
## 1640 32785426376.5332 nan 0.0100 -15201092.9494
## 1660 32629356670.8637 nan 0.0100 -3131289.3688
## 1680 32504784319.6778 nan 0.0100 -7401626.9883
## 1700 32389820842.0069 nan 0.0100 -16641974.2017
## 1720 32255691822.1700 nan 0.0100 -21042615.0395
## 1740 32136816993.4954 nan 0.0100 3084810.1356
## 1760 32033512987.0033 nan 0.0100 1498812.6427
## 1780 31937310477.7542 nan 0.0100 -26316516.9991
## 1800 31825137764.7394 nan 0.0100 -7026619.1515
## 1820 31731055981.0724 nan 0.0100 -4027722.0670
## 1840 31599890205.1978 nan 0.0100 -7550517.4375
## 1860 31494472370.5039 nan 0.0100 -10304926.2151
## 1880 31387802225.4166 nan 0.0100 -951776.6866
## 1900 31307417983.0881 nan 0.0100 1116108.9515
## 1920 31187692411.5216 nan 0.0100 -1063060.6567
## 1940 31052917278.5437 nan 0.0100 -8091641.6655
## 1960 30987047062.3699 nan 0.0100 -174917.8883
## 1980 30858556419.3985 nan 0.0100 -5844301.6950
## 2000 30767733764.8096 nan 0.0100 -4484296.6254
## 2020 30662784439.0100 nan 0.0100 -23337791.6420
## 2040 30572921788.8292 nan 0.0100 531443.7347
## 2060 30464158622.3199 nan 0.0100 -18838940.6576
## 2080 30362313308.1299 nan 0.0100 -17900523.2811
## 2100 30287047796.8080 nan 0.0100 -3950268.9955
## 2120 30174520951.7201 nan 0.0100 -7623740.2307
## 2140 30077987714.7994 nan 0.0100 -13612399.7789
## 2160 29981978758.2186 nan 0.0100 -18900721.4087
## 2180 29897296471.0534 nan 0.0100 -2486725.2026
## 2200 29797903125.4608 nan 0.0100 -6828765.1957
## 2220 29712895024.2468 nan 0.0100 -20675309.0133
## 2240 29621190771.1299 nan 0.0100 -4996237.0010
## 2260 29532769471.9314 nan 0.0100 -20761139.4914
## 2280 29466155653.4571 nan 0.0100 -14906985.6915
## 2300 29382576099.9856 nan 0.0100 -14127778.6596
## 2320 29295064180.0091 nan 0.0100 -9294500.9611
## 2340 29208177960.8657 nan 0.0100 -22590415.7012
## 2360 29111213059.1656 nan 0.0100 -10931470.3574
## 2380 29005972448.9217 nan 0.0100 -10889670.5874
## 2400 28938121511.2585 nan 0.0100 -24744360.4599
## 2420 28858011965.8188 nan 0.0100 -7021369.6531
## 2440 28777840211.1020 nan 0.0100 -10586432.6291
## 2460 28701990027.1903 nan 0.0100 2894860.3297
## 2480 28607867305.5863 nan 0.0100 -9957959.0297
## 2500 28532351204.1765 nan 0.0100 -13207041.3870
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 260643513482.6015 nan 0.0100 2847156679.7299
## 2 257432023047.3648 nan 0.0100 2603887810.6893
## 3 254478687255.1945 nan 0.0100 2859736934.9993
## 4 251567252716.5815 nan 0.0100 3291765860.1277
## 5 248531191305.3941 nan 0.0100 2468043611.5343
## 6 245684394159.9281 nan 0.0100 2785892892.3899
## 7 242896213440.2664 nan 0.0100 2527353133.0937
## 8 240038347081.9065 nan 0.0100 1886010789.5063
## 9 237284755851.9253 nan 0.0100 2343085105.8254
## 10 234513391270.3984 nan 0.0100 2518929879.3735
## 20 210247149888.1555 nan 0.0100 1608075149.5004
## 40 172827266628.4699 nan 0.0100 1560805830.1499
## 60 145218564963.9279 nan 0.0100 1154681297.7380
## 80 124404713122.5600 nan 0.0100 1049020213.9421
## 100 108742450053.0080 nan 0.0100 832001390.0465
## 120 96562667009.9313 nan 0.0100 482540212.4430
## 140 86550243026.3862 nan 0.0100 321259938.3259
## 160 78335924910.8324 nan 0.0100 242181203.6886
## 180 71617858252.8672 nan 0.0100 231570752.9519
## 200 66306065377.8045 nan 0.0100 280652119.2549
## 220 61704751122.1477 nan 0.0100 11328273.1927
## 240 57887670368.0715 nan 0.0100 153707430.1549
## 260 54749996599.1019 nan 0.0100 101922797.5465
## 280 52028809939.5021 nan 0.0100 94693924.7721
## 300 49686372777.1556 nan 0.0100 23276483.2488
## 320 47656348025.1158 nan 0.0100 30694584.1692
## 340 45978526886.3737 nan 0.0100 74634161.3612
## 360 44610465573.8573 nan 0.0100 -2993167.1208
## 380 43364262852.1142 nan 0.0100 19669727.6651
## 400 42315624153.9760 nan 0.0100 5595390.1893
## 420 41368170177.3766 nan 0.0100 5709202.0890
## 440 40509643467.8855 nan 0.0100 -18127542.5453
## 460 39744802176.3768 nan 0.0100 29125308.2760
## 480 39035549803.3342 nan 0.0100 14497344.0947
## 500 38384628620.0371 nan 0.0100 10943060.6555
## 520 37820371693.6224 nan 0.0100 20524087.6593
## 540 37283168439.4497 nan 0.0100 20868714.1267
## 560 36814934688.2581 nan 0.0100 112238.0584
## 580 36374819469.9264 nan 0.0100 -14301557.3808
## 600 35940845793.8411 nan 0.0100 -9855851.5132
## 620 35536779051.9916 nan 0.0100 12383654.2367
## 640 35161824870.0916 nan 0.0100 -6507314.3054
## 660 34798418856.2307 nan 0.0100 2595651.4524
## 680 34414132783.3327 nan 0.0100 9665128.9988
## 700 34054560074.8712 nan 0.0100 -6021640.4216
## 720 33700077337.9356 nan 0.0100 -15092568.9788
## 740 33399638128.4842 nan 0.0100 -687147.5704
## 760 33089464278.3176 nan 0.0100 -27402831.0803
## 780 32827449680.7344 nan 0.0100 -3218709.9675
## 800 32580245115.1036 nan 0.0100 2106357.2044
## 820 32312737557.8373 nan 0.0100 -16823560.8228
## 840 32037019360.9582 nan 0.0100 -11803732.4346
## 860 31764366648.3159 nan 0.0100 -1199272.0716
## 880 31527485014.5437 nan 0.0100 -2842049.3764
## 900 31236276667.8318 nan 0.0100 -14297922.5909
## 920 30997762927.4382 nan 0.0100 7330340.1157
## 940 30782167931.3198 nan 0.0100 5016502.4031
## 960 30573175419.4616 nan 0.0100 1520846.6648
## 980 30367115270.9659 nan 0.0100 -3399177.2660
## 1000 30152613865.6440 nan 0.0100 2837440.4952
## 1020 29946323347.3931 nan 0.0100 -13100104.3385
## 1040 29755193199.8846 nan 0.0100 -31450419.5571
## 1060 29528840972.3809 nan 0.0100 4601705.9919
## 1080 29347421484.5568 nan 0.0100 -38390662.1226
## 1100 29162544145.8176 nan 0.0100 -13859961.5273
## 1120 28942003353.9230 nan 0.0100 1340855.9394
## 1140 28780040508.4916 nan 0.0100 -9097742.8836
## 1160 28596125161.9557 nan 0.0100 -6437445.9113
## 1180 28432402544.6226 nan 0.0100 -528295.6411
## 1200 28246506607.2953 nan 0.0100 -19105528.2989
## 1220 28051666858.8599 nan 0.0100 -40120688.7340
## 1240 27842286445.4797 nan 0.0100 4499099.8645
## 1260 27685363823.4298 nan 0.0100 -28918810.7817
## 1280 27506506714.6187 nan 0.0100 4588298.1387
## 1300 27338245437.6016 nan 0.0100 -7700508.0814
## 1320 27193477158.3503 nan 0.0100 831895.8522
## 1340 27028487268.4764 nan 0.0100 -2615254.7069
## 1360 26869505542.2190 nan 0.0100 -18185095.7546
## 1380 26724703310.3511 nan 0.0100 -12900692.6979
## 1400 26589551924.7536 nan 0.0100 801285.1435
## 1420 26440433684.6818 nan 0.0100 -6097167.3276
## 1440 26284057209.3325 nan 0.0100 -7343607.4767
## 1460 26114036457.6690 nan 0.0100 -10489898.7288
## 1480 25940355674.9748 nan 0.0100 -10102849.4125
## 1500 25805942401.8245 nan 0.0100 -6855507.8347
## 1520 25650801765.1141 nan 0.0100 -9924927.1445
## 1540 25518923409.0750 nan 0.0100 1166143.1886
## 1560 25375434280.5571 nan 0.0100 -2484245.5282
## 1580 25267586291.6231 nan 0.0100 478237.8515
## 1600 25152401350.0376 nan 0.0100 3691872.4376
## 1620 25034541881.4856 nan 0.0100 -16101683.3175
## 1640 24917339869.0712 nan 0.0100 -13568514.5185
## 1660 24786620850.1565 nan 0.0100 -603589.5283
## 1680 24660389106.4028 nan 0.0100 1168834.2794
## 1700 24554076384.6345 nan 0.0100 -12928341.6346
## 1720 24430177167.5950 nan 0.0100 -879095.0016
## 1740 24315814210.4057 nan 0.0100 774450.6214
## 1760 24205377016.3885 nan 0.0100 -21514649.7384
## 1780 24080766964.3365 nan 0.0100 -16873249.2667
## 1800 23970224264.2122 nan 0.0100 -5546393.9793
## 1820 23841542459.5424 nan 0.0100 -11499072.8521
## 1840 23723535306.8962 nan 0.0100 118058.6068
## 1860 23609276186.6364 nan 0.0100 -18037229.8402
## 1880 23510995239.3934 nan 0.0100 -12345142.3074
## 1900 23415720085.9346 nan 0.0100 -6612197.6620
## 1920 23318708501.8748 nan 0.0100 -7809321.2552
## 1940 23197748935.1561 nan 0.0100 -10328135.2530
## 1960 23089756991.1678 nan 0.0100 -21274343.9130
## 1980 22999773785.9131 nan 0.0100 -9668646.4625
## 2000 22893679492.5828 nan 0.0100 -5773158.3179
## 2020 22791775890.4895 nan 0.0100 -5983660.5190
## 2040 22704027904.0505 nan 0.0100 -14392278.4580
## 2060 22627276003.3325 nan 0.0100 -4058974.2815
## 2080 22527638336.9320 nan 0.0100 -16473451.6673
## 2100 22428258099.2054 nan 0.0100 -8141675.6053
## 2120 22340843750.1526 nan 0.0100 -2330783.3019
## 2140 22243295745.5837 nan 0.0100 -3139012.6174
## 2160 22170055391.1141 nan 0.0100 -5567889.4583
## 2180 22079867898.8795 nan 0.0100 -2306299.6021
## 2200 21991529848.4466 nan 0.0100 -10759657.8813
## 2220 21898270473.7084 nan 0.0100 -6414305.7333
## 2240 21816796102.3612 nan 0.0100 -4068983.3036
## 2260 21717253600.4306 nan 0.0100 -6581857.1098
## 2280 21630030264.7820 nan 0.0100 -2127745.4707
## 2300 21554568157.6359 nan 0.0100 -368238.8914
## 2320 21465841649.0669 nan 0.0100 -372205.3791
## 2340 21377392228.6327 nan 0.0100 -6917206.7467
## 2360 21303432977.3077 nan 0.0100 -8272908.9783
## 2380 21215909374.0472 nan 0.0100 -10244714.3646
## 2400 21138129599.2691 nan 0.0100 -8133891.7957
## 2420 21058088107.5848 nan 0.0100 -3844293.1252
## 2440 20976999593.2331 nan 0.0100 -3227936.0673
## 2460 20886678614.0019 nan 0.0100 -8350774.5922
## 2480 20811049392.6491 nan 0.0100 -8501747.6469
## 2500 20733558015.6276 nan 0.0100 425818.3129
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 259166663653.2664 nan 0.0010 158387676.8067
## 2 258998949621.3611 nan 0.0010 173870027.3698
## 3 258825857677.7079 nan 0.0010 139736480.8757
## 4 258657877256.1200 nan 0.0010 156366688.5925
## 5 258492569200.5462 nan 0.0010 194161231.4777
## 6 258329543776.4801 nan 0.0010 190848424.2098
## 7 258158867645.3405 nan 0.0010 155287480.3841
## 8 257997599598.1236 nan 0.0010 169455494.6150
## 9 257836508928.1519 nan 0.0010 179092634.4410
## 10 257664252544.9071 nan 0.0010 160758204.4315
## 20 256015674409.0833 nan 0.0010 164597438.1230
## 40 252807203307.7701 nan 0.0010 160533119.7545
## 60 249713676723.8922 nan 0.0010 164895273.2771
## 80 246734480334.1288 nan 0.0010 130887738.3585
## 100 243804993547.7397 nan 0.0010 153199934.7300
## 120 241047576829.9063 nan 0.0010 148090884.8848
## 140 238337819403.3540 nan 0.0010 132032772.5835
## 160 235721917604.3087 nan 0.0010 125598342.7536
## 180 233186123854.9005 nan 0.0010 112123057.6947
## 200 230734084981.7777 nan 0.0010 124831636.0433
## 220 228352153838.9761 nan 0.0010 106653627.4017
## 240 226058373379.0519 nan 0.0010 101313099.3214
## 260 223816398894.5467 nan 0.0010 93964253.3975
## 280 221628380934.5453 nan 0.0010 106113190.3972
## 300 219526925017.9182 nan 0.0010 101528656.8352
## 320 217458935549.7411 nan 0.0010 75247159.7392
## 340 215459735219.3710 nan 0.0010 90793450.0946
## 360 213497792252.7570 nan 0.0010 98247007.0609
## 380 211617047469.5461 nan 0.0010 98655509.3788
## 400 209743892261.8989 nan 0.0010 63903476.1466
## 420 207937026911.9603 nan 0.0010 64103776.6722
## 440 206190327544.2157 nan 0.0010 85911763.7489
## 460 204492984214.7758 nan 0.0010 82540872.7565
## 480 202852869015.9210 nan 0.0010 76456703.9099
## 500 201251416443.4606 nan 0.0010 81983184.4652
## 520 199679294055.7394 nan 0.0010 77008652.6418
## 540 198150323963.0636 nan 0.0010 73742687.3485
## 560 196647683531.1810 nan 0.0010 67995484.0601
## 580 195173538500.5806 nan 0.0010 55904244.1017
## 600 193749818633.9117 nan 0.0010 60427316.5895
## 620 192379195950.8802 nan 0.0010 65942623.9921
## 640 191036035915.7223 nan 0.0010 44341976.8764
## 660 189721009457.1834 nan 0.0010 40784184.9197
## 680 188437933303.5312 nan 0.0010 60150489.1040
## 700 187184835745.2557 nan 0.0010 65006969.6717
## 720 185960781711.6473 nan 0.0010 63671311.7711
## 740 184733258012.5540 nan 0.0010 44886416.1833
## 760 183565264584.5247 nan 0.0010 59219200.5859
## 780 182440281782.6235 nan 0.0010 56166049.1847
## 800 181332827027.0840 nan 0.0010 55721578.3427
## 820 180228301898.6654 nan 0.0010 55450882.1243
## 840 179164592293.4020 nan 0.0010 49250286.5658
## 860 178109675289.6119 nan 0.0010 49738805.2280
## 880 177063025203.5014 nan 0.0010 54684827.9046
## 900 176024454965.2932 nan 0.0010 49507467.6046
## 920 175007058196.3516 nan 0.0010 34932902.2989
## 940 174026426345.4328 nan 0.0010 50559061.9421
## 960 173045756442.4836 nan 0.0010 46622178.8369
## 980 172083751858.3968 nan 0.0010 38357730.4192
## 1000 171130307527.5830 nan 0.0010 50782183.6774
## 1020 170198001784.2536 nan 0.0010 44270317.3864
## 1040 169272286070.6767 nan 0.0010 43599723.1381
## 1060 168367856886.9087 nan 0.0010 41113275.8620
## 1080 167471183609.6512 nan 0.0010 26499292.7452
## 1100 166596083490.2549 nan 0.0010 22057000.9833
## 1120 165730176298.1363 nan 0.0010 39101907.6983
## 1140 164893698926.0862 nan 0.0010 19482941.2693
## 1160 164051110322.1299 nan 0.0010 40735207.7306
## 1180 163240524731.0112 nan 0.0010 34065644.2465
## 1200 162414659038.9416 nan 0.0010 37389563.0335
## 1220 161613794969.0412 nan 0.0010 20729379.8566
## 1240 160817096628.4514 nan 0.0010 32129205.3609
## 1260 160035149392.2575 nan 0.0010 32618534.5385
## 1280 159274954917.7206 nan 0.0010 21612692.3151
## 1300 158524428069.0334 nan 0.0010 14867317.5156
## 1320 157765775199.9459 nan 0.0010 36024555.9786
## 1340 157033023748.2316 nan 0.0010 36023512.3067
## 1360 156307667594.6556 nan 0.0010 30647857.6636
## 1380 155581307398.7742 nan 0.0010 30863367.1993
## 1400 154870667596.8123 nan 0.0010 34552587.6640
## 1420 154167746826.0142 nan 0.0010 28384072.3326
## 1440 153476232252.9948 nan 0.0010 29679040.3752
## 1460 152793256201.2714 nan 0.0010 11407036.6076
## 1480 152109133984.1469 nan 0.0010 34330479.7371
## 1500 151444272659.8763 nan 0.0010 21102500.8544
## 1520 150784109002.5326 nan 0.0010 21949463.7146
## 1540 150126138203.5594 nan 0.0010 28884599.0482
## 1560 149470808040.6111 nan 0.0010 23574428.8902
## 1580 148836298493.8170 nan 0.0010 28611265.5747
## 1600 148196993066.5724 nan 0.0010 32935097.2968
## 1620 147562958456.5246 nan 0.0010 24221565.9634
## 1640 146943924566.3988 nan 0.0010 24359196.8549
## 1660 146333099532.5141 nan 0.0010 30412057.3395
## 1680 145723752674.6317 nan 0.0010 22805343.8916
## 1700 145124361551.3756 nan 0.0010 30948490.9309
## 1720 144518578097.6644 nan 0.0010 20952867.3558
## 1740 143932326378.5960 nan 0.0010 25673057.9006
## 1760 143354950674.0786 nan 0.0010 24641511.0225
## 1780 142777229980.2881 nan 0.0010 17446873.6772
## 1800 142228101372.7609 nan 0.0010 25814225.3649
## 1820 141670371430.5333 nan 0.0010 27932632.5909
## 1840 141114615972.6858 nan 0.0010 20874152.6895
## 1860 140567710695.2216 nan 0.0010 19459867.3112
## 1880 140030354805.5406 nan 0.0010 21434549.2648
## 1900 139487459705.0050 nan 0.0010 24336873.1481
## 1920 138952787899.6801 nan 0.0010 20329939.2228
## 1940 138430257016.7114 nan 0.0010 15279222.7115
## 1960 137915759383.9774 nan 0.0010 18396063.9496
## 1980 137404401752.4398 nan 0.0010 23744414.1076
## 2000 136896095389.6431 nan 0.0010 25244070.8957
## 2020 136393861312.0005 nan 0.0010 24896981.1794
## 2040 135895318801.2157 nan 0.0010 25034983.6150
## 2060 135403495644.0709 nan 0.0010 16515519.6619
## 2080 134920632303.4060 nan 0.0010 428774.0293
## 2100 134441372867.1284 nan 0.0010 18569450.0995
## 2120 133956822757.1455 nan 0.0010 13728337.7137
## 2140 133487542413.7294 nan 0.0010 26525888.8577
## 2160 133021509255.7203 nan 0.0010 23466529.6407
## 2180 132555614083.0189 nan 0.0010 22809077.7790
## 2200 132091021987.4893 nan 0.0010 21091437.5470
## 2220 131638647372.4035 nan 0.0010 13141977.8950
## 2240 131193704651.0022 nan 0.0010 23755625.1559
## 2260 130749903461.3046 nan 0.0010 11569852.5301
## 2280 130316212061.0515 nan 0.0010 15282578.2965
## 2300 129887183158.0386 nan 0.0010 21724685.5519
## 2320 129449015440.3340 nan 0.0010 19511613.9818
## 2340 129018192961.2002 nan 0.0010 12519347.7222
## 2360 128604277115.4884 nan 0.0010 20803587.3425
## 2380 128187424772.9316 nan 0.0010 12344192.3629
## 2400 127782372181.8285 nan 0.0010 21414127.4205
## 2420 127383149164.0753 nan 0.0010 17935384.0684
## 2440 126975118274.8312 nan 0.0010 8620336.3369
## 2460 126576268742.2216 nan 0.0010 13184299.9687
## 2480 126174079270.4531 nan 0.0010 16441893.8257
## 2500 125787675297.2055 nan 0.0010 15028424.3685
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 259072157451.4715 nan 0.0010 252337789.4860
## 2 258803414554.1534 nan 0.0010 173278908.1643
## 3 258539223079.1067 nan 0.0010 204327387.3594
## 4 258270857405.1219 nan 0.0010 276119315.4399
## 5 257999021263.9653 nan 0.0010 261786450.5838
## 6 257733724536.3110 nan 0.0010 284513689.4904
## 7 257475691073.1387 nan 0.0010 246617600.9783
## 8 257221157128.5137 nan 0.0010 275521037.5787
## 9 256968040704.2645 nan 0.0010 272544170.3635
## 10 256698277493.9476 nan 0.0010 260636938.7885
## 20 254100334020.0159 nan 0.0010 254302618.7061
## 40 249061863666.9465 nan 0.0010 254729078.9354
## 60 244111120877.9872 nan 0.0010 184701768.7099
## 80 239412533742.6068 nan 0.0010 218608422.2861
## 100 234854579100.9936 nan 0.0010 187537261.0555
## 120 230433718148.7845 nan 0.0010 189283525.1707
## 140 226180172092.8811 nan 0.0010 159402448.8358
## 160 222030801722.0708 nan 0.0010 177867913.7217
## 180 218046858905.9646 nan 0.0010 247448072.8634
## 200 214175013386.5316 nan 0.0010 165394386.9483
## 220 210411584583.2428 nan 0.0010 165297228.7807
## 240 206763459280.3245 nan 0.0010 184939315.0670
## 260 203251883605.0417 nan 0.0010 169539208.3805
## 280 199830668669.6650 nan 0.0010 145815314.9424
## 300 196538070040.6517 nan 0.0010 135808676.7741
## 320 193350508737.7537 nan 0.0010 179878937.4341
## 340 190242282029.9467 nan 0.0010 137814263.8348
## 360 187264895676.0939 nan 0.0010 128918088.0470
## 380 184338949031.0264 nan 0.0010 138698120.4874
## 400 181493156299.1855 nan 0.0010 126793325.3145
## 420 178715221520.5701 nan 0.0010 148451772.3511
## 440 176069044982.4795 nan 0.0010 141245319.5430
## 460 173431592922.0760 nan 0.0010 160412624.3849
## 480 170901993787.4499 nan 0.0010 106545032.5462
## 500 168425243549.5626 nan 0.0010 132348295.3555
## 520 166012167803.7043 nan 0.0010 95215000.5660
## 540 163689443024.0967 nan 0.0010 136377206.2174
## 560 161371131759.0139 nan 0.0010 96391731.7836
## 580 159167239698.1578 nan 0.0010 101376353.0039
## 600 157018648984.6294 nan 0.0010 100192295.2634
## 620 154916166627.4012 nan 0.0010 72589054.4880
## 640 152849142321.5450 nan 0.0010 101045011.2301
## 660 150834110731.4417 nan 0.0010 85769319.9633
## 680 148907270969.0066 nan 0.0010 88582973.6540
## 700 147025352412.8214 nan 0.0010 86223221.8330
## 720 145147985678.4128 nan 0.0010 91630595.0053
## 740 143268226742.8454 nan 0.0010 94203654.6189
## 760 141480617182.2491 nan 0.0010 64223779.7211
## 780 139735439018.0238 nan 0.0010 71590027.9850
## 800 138040266320.4223 nan 0.0010 58341781.1036
## 820 136369546416.3825 nan 0.0010 72873946.2678
## 840 134772691834.7719 nan 0.0010 98144495.1092
## 860 133196622788.8537 nan 0.0010 67633027.9552
## 880 131651966751.0590 nan 0.0010 66511961.4014
## 900 130127175371.7215 nan 0.0010 90080945.1065
## 920 128648169470.6160 nan 0.0010 43301131.5024
## 940 127200105055.0592 nan 0.0010 65457489.7047
## 960 125772959757.6684 nan 0.0010 60045690.9883
## 980 124405035208.1665 nan 0.0010 47119767.3888
## 1000 123071155920.9291 nan 0.0010 58623515.2805
## 1020 121728375356.3816 nan 0.0010 71189506.8506
## 1040 120440835908.1551 nan 0.0010 55733668.8523
## 1060 119194587352.2634 nan 0.0010 55673599.5638
## 1080 117946537284.3986 nan 0.0010 65914959.0460
## 1100 116737688348.4260 nan 0.0010 48632189.0079
## 1120 115546164786.2548 nan 0.0010 45707960.8813
## 1140 114400115847.4329 nan 0.0010 56620408.4493
## 1160 113272791447.7361 nan 0.0010 58890649.4160
## 1180 112183039682.6405 nan 0.0010 48312926.7038
## 1200 111109034044.0710 nan 0.0010 52225971.6376
## 1220 110031868487.8640 nan 0.0010 55095192.8822
## 1240 109002040201.0020 nan 0.0010 50685068.1706
## 1260 107988744009.0313 nan 0.0010 41773213.9214
## 1280 106990755173.4104 nan 0.0010 49585198.0814
## 1300 105971907174.7103 nan 0.0010 49891175.7160
## 1320 104983058999.3150 nan 0.0010 49386968.0162
## 1340 104025244096.4341 nan 0.0010 43660466.7455
## 1360 103093031161.4550 nan 0.0010 21791458.2856
## 1380 102187106535.6277 nan 0.0010 25257148.7961
## 1400 101271269206.5851 nan 0.0010 37389708.9920
## 1420 100394512089.1302 nan 0.0010 36669300.8943
## 1440 99501801945.9834 nan 0.0010 22577646.1740
## 1460 98650652369.8075 nan 0.0010 42309260.9687
## 1480 97803559038.1818 nan 0.0010 49295819.1038
## 1500 96976968441.5391 nan 0.0010 30524107.8997
## 1520 96170595442.8129 nan 0.0010 39146762.5589
## 1540 95386501812.0281 nan 0.0010 36657786.7392
## 1560 94582869757.3694 nan 0.0010 35077402.9716
## 1580 93798088819.8883 nan 0.0010 24740215.7662
## 1600 93027038051.5789 nan 0.0010 30721972.4893
## 1620 92264861113.8537 nan 0.0010 41859620.3076
## 1640 91503213870.1743 nan 0.0010 24562623.1613
## 1660 90748677395.4762 nan 0.0010 65895505.3860
## 1680 90018584842.1755 nan 0.0010 14877307.4508
## 1700 89297868341.0164 nan 0.0010 28841518.4447
## 1720 88573831078.2089 nan 0.0010 29341421.9262
## 1740 87879984654.3538 nan 0.0010 22367033.7512
## 1760 87207193719.4358 nan 0.0010 16953022.7456
## 1780 86538313601.2425 nan 0.0010 48145403.0832
## 1800 85878655646.6298 nan 0.0010 24658859.6207
## 1820 85226098462.4830 nan 0.0010 15361423.0926
## 1840 84586073499.5806 nan 0.0010 18929422.7201
## 1860 83935657810.5628 nan 0.0010 22902120.0826
## 1880 83295660078.6306 nan 0.0010 41072367.3638
## 1900 82675964121.0414 nan 0.0010 31289460.3538
## 1920 82096302210.8026 nan 0.0010 22684019.6325
## 1940 81482187257.5066 nan 0.0010 35805322.7143
## 1960 80893257571.6400 nan 0.0010 17410353.6983
## 1980 80309890852.2455 nan 0.0010 32799497.5129
## 2000 79749509238.0328 nan 0.0010 19251984.1234
## 2020 79193625529.9530 nan 0.0010 11887821.1404
## 2040 78626219238.2245 nan 0.0010 24849054.1396
## 2060 78058324339.4713 nan 0.0010 38592442.7009
## 2080 77525910488.0982 nan 0.0010 23352327.5860
## 2100 76983789971.9226 nan 0.0010 26941471.2861
## 2120 76444950890.8766 nan 0.0010 21184109.4132
## 2140 75926786427.5326 nan 0.0010 19954708.4975
## 2160 75385057976.3984 nan 0.0010 25516668.5475
## 2180 74900456504.6297 nan 0.0010 14468005.9851
## 2200 74390361208.3584 nan 0.0010 24960145.5196
## 2220 73903648966.8464 nan 0.0010 15358405.4568
## 2240 73408414364.5706 nan 0.0010 12075376.2059
## 2260 72925648809.5494 nan 0.0010 7619961.3210
## 2280 72479579854.2561 nan 0.0010 10919664.2835
## 2300 72003456091.8353 nan 0.0010 18257551.0162
## 2320 71553346399.1774 nan 0.0010 23205832.3499
## 2340 71097932297.8313 nan 0.0010 21755062.0289
## 2360 70647159375.9429 nan 0.0010 25743125.5307
## 2380 70203789902.4117 nan 0.0010 18451378.4211
## 2400 69770095611.4147 nan 0.0010 16800821.0386
## 2420 69354377543.8908 nan 0.0010 6245556.7315
## 2440 68938236316.1187 nan 0.0010 26559307.5156
## 2460 68524107145.2995 nan 0.0010 13604179.7692
## 2480 68110487809.0724 nan 0.0010 20612437.8038
## 2500 67725179702.5552 nan 0.0010 12601513.4470
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 259024706148.1869 nan 0.0010 202341648.1355
## 2 258716166008.0942 nan 0.0010 233319711.4639
## 3 258410336212.6458 nan 0.0010 296598559.2709
## 4 258111404613.5975 nan 0.0010 281227060.1258
## 5 257807390205.7437 nan 0.0010 270214837.4257
## 6 257503315158.8519 nan 0.0010 311423270.3675
## 7 257197388123.7276 nan 0.0010 264761262.3958
## 8 256887834704.1630 nan 0.0010 265122500.1244
## 9 256585614161.8640 nan 0.0010 282261389.9388
## 10 256294177919.0562 nan 0.0010 357676043.0135
## 20 253295076192.2123 nan 0.0010 261444820.2354
## 40 247435520662.8283 nan 0.0010 241456000.0108
## 60 241763412402.6063 nan 0.0010 246974438.7817
## 80 236395186302.0016 nan 0.0010 267227855.5305
## 100 231087119621.4608 nan 0.0010 255863706.0830
## 120 225987997564.2108 nan 0.0010 248901707.0945
## 140 221102668133.7592 nan 0.0010 225283664.6840
## 160 216289526569.9433 nan 0.0010 180746238.4629
## 180 211674390430.3870 nan 0.0010 231326760.6102
## 200 207231893365.5473 nan 0.0010 185048738.7223
## 220 202956537865.1679 nan 0.0010 182866875.5760
## 240 198779497476.1069 nan 0.0010 186342087.3965
## 260 194765285684.1902 nan 0.0010 232756187.2469
## 280 190876853305.6195 nan 0.0010 144991823.6406
## 300 187106408456.8798 nan 0.0010 179744815.7753
## 320 183462611277.3154 nan 0.0010 177225325.7900
## 340 179883155985.5074 nan 0.0010 191294049.5514
## 360 176422562765.3166 nan 0.0010 165530408.5569
## 380 173060505758.9583 nan 0.0010 147808990.4475
## 400 169809238618.3125 nan 0.0010 150566263.7738
## 420 166700396884.5856 nan 0.0010 161553151.4296
## 440 163650063454.7106 nan 0.0010 130669254.1476
## 460 160670864445.0939 nan 0.0010 135736141.6190
## 480 157762944056.4209 nan 0.0010 131372863.7180
## 500 154966870060.3140 nan 0.0010 134142316.2856
## 520 152251660861.6629 nan 0.0010 112604976.4341
## 540 149630066033.1541 nan 0.0010 138274921.1479
## 560 147084757590.4272 nan 0.0010 62523031.2023
## 580 144613198764.9211 nan 0.0010 105152902.7137
## 600 142206548183.8018 nan 0.0010 112717789.8072
## 620 139902482421.7046 nan 0.0010 119669206.2931
## 640 137632835688.8451 nan 0.0010 102857598.9976
## 660 135416205280.1470 nan 0.0010 68640222.5089
## 680 133304040212.3327 nan 0.0010 90705387.8752
## 700 131225716593.8080 nan 0.0010 98725774.7350
## 720 129207814447.0452 nan 0.0010 96679405.4107
## 740 127245207847.8147 nan 0.0010 55676422.5491
## 760 125354517733.9771 nan 0.0010 64441932.6822
## 780 123482037683.4347 nan 0.0010 84176329.3622
## 800 121676659313.8885 nan 0.0010 80782562.0443
## 820 119897834588.1114 nan 0.0010 89455157.5301
## 840 118160282982.0817 nan 0.0010 84937039.2229
## 860 116486619138.8203 nan 0.0010 94430966.6262
## 880 114837518098.5079 nan 0.0010 64614910.3979
## 900 113230675417.1619 nan 0.0010 69091512.4525
## 920 111692079196.3463 nan 0.0010 77686294.6605
## 940 110166775588.0905 nan 0.0010 45374960.3954
## 960 108680075228.1972 nan 0.0010 53958189.4288
## 980 107237942416.2732 nan 0.0010 58597470.6399
## 1000 105808040226.7600 nan 0.0010 72060636.8816
## 1020 104452773902.1480 nan 0.0010 50068270.0113
## 1040 103104031535.4841 nan 0.0010 48409854.6428
## 1060 101799861421.7267 nan 0.0010 51307559.6257
## 1080 100531295960.4051 nan 0.0010 53949268.5085
## 1100 99278267298.1817 nan 0.0010 44004260.6027
## 1120 98046047299.8637 nan 0.0010 31946638.6688
## 1140 96832462203.8978 nan 0.0010 52023984.4317
## 1160 95654971853.0179 nan 0.0010 41249395.8649
## 1180 94523430275.9780 nan 0.0010 31793769.5155
## 1200 93397444988.0342 nan 0.0010 51079853.3281
## 1220 92318854408.3407 nan 0.0010 46584029.9714
## 1240 91272305037.4966 nan 0.0010 43322958.1782
## 1260 90199923951.9090 nan 0.0010 32674278.5563
## 1280 89179652323.3983 nan 0.0010 43296963.3439
## 1300 88186402343.0536 nan 0.0010 46949561.9852
## 1320 87229391138.3787 nan 0.0010 46253946.3849
## 1340 86264915567.6454 nan 0.0010 47453252.7761
## 1360 85326493925.8459 nan 0.0010 29831148.8655
## 1380 84402755737.6023 nan 0.0010 46484419.5318
## 1400 83510142347.0434 nan 0.0010 42963990.3448
## 1420 82640715276.0373 nan 0.0010 36442431.4856
## 1440 81786167381.6717 nan 0.0010 52524529.0426
## 1460 80937112377.1544 nan 0.0010 24394511.5254
## 1480 80131336010.7317 nan 0.0010 35651209.1741
## 1500 79332123053.1479 nan 0.0010 28978943.5477
## 1520 78534222487.1384 nan 0.0010 25468813.7163
## 1540 77759903513.4940 nan 0.0010 17223027.2970
## 1560 76988142430.2315 nan 0.0010 36284826.5813
## 1580 76253893380.1910 nan 0.0010 20802511.7627
## 1600 75527497187.8209 nan 0.0010 23402358.5241
## 1620 74820575270.8305 nan 0.0010 23310165.9941
## 1640 74111996863.4131 nan 0.0010 30935604.0089
## 1660 73434508175.9756 nan 0.0010 30070522.0216
## 1680 72748529130.0309 nan 0.0010 16110834.3430
## 1700 72106624298.8084 nan 0.0010 20877738.8984
## 1720 71446988949.3288 nan 0.0010 28832025.6610
## 1740 70822088683.3411 nan 0.0010 21911749.3669
## 1760 70195175351.3423 nan 0.0010 24396532.1070
## 1780 69576178798.0461 nan 0.0010 27866753.4567
## 1800 68978358437.1642 nan 0.0010 16513226.8830
## 1820 68387263654.8369 nan 0.0010 21853343.6440
## 1840 67794683320.8512 nan 0.0010 34645398.5988
## 1860 67239422834.9042 nan 0.0010 21440473.5622
## 1880 66665554178.1037 nan 0.0010 23555939.4387
## 1900 66127093814.3493 nan 0.0010 22139598.7576
## 1920 65601779885.1847 nan 0.0010 17611578.9445
## 1940 65074557516.2660 nan 0.0010 21792613.3740
## 1960 64559267257.6159 nan 0.0010 14261318.8565
## 1980 64048431604.9002 nan 0.0010 17279299.4642
## 2000 63553528747.3629 nan 0.0010 26832362.5663
## 2020 63064199867.8609 nan 0.0010 15728376.1531
## 2040 62595420434.4504 nan 0.0010 11857908.2456
## 2060 62136513850.4699 nan 0.0010 18013338.1771
## 2080 61676793365.7809 nan 0.0010 15076633.2192
## 2100 61218545902.7558 nan 0.0010 20613682.4529
## 2120 60777114523.9639 nan 0.0010 12644721.0583
## 2140 60358201074.2739 nan 0.0010 15747432.0600
## 2160 59931328835.6893 nan 0.0010 18836172.2955
## 2180 59512856814.0746 nan 0.0010 9690365.2770
## 2200 59088302767.0196 nan 0.0010 18645512.2936
## 2220 58685759507.8632 nan 0.0010 11883070.2572
## 2240 58277834202.4178 nan 0.0010 14986349.6005
## 2260 57871283669.6141 nan 0.0010 18519559.6112
## 2280 57498077506.3413 nan 0.0010 12180386.3662
## 2300 57115762444.5963 nan 0.0010 11991853.8949
## 2320 56745058810.4761 nan 0.0010 14061895.4090
## 2340 56400142255.8631 nan 0.0010 8918248.1378
## 2360 56046350311.3943 nan 0.0010 5078172.9672
## 2380 55693033977.3388 nan 0.0010 8091583.4611
## 2400 55355334754.7163 nan 0.0010 7775686.4750
## 2420 55013681070.7978 nan 0.0010 19015977.9399
## 2440 54675945504.3272 nan 0.0010 12978893.0390
## 2460 54348059765.6459 nan 0.0010 21178539.9105
## 2480 54031178047.3145 nan 0.0010 11629525.8195
## 2500 53728861820.5850 nan 0.0010 22315577.2179
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 257619365834.2645 nan 0.0100 1670540197.5444
## 2 255969916859.3740 nan 0.0100 1530714053.8846
## 3 254360207510.4393 nan 0.0100 1608370441.6415
## 4 252764142338.3500 nan 0.0100 1669694478.2263
## 5 251248074612.6969 nan 0.0100 1521574864.2217
## 6 249728826507.3120 nan 0.0100 1574490799.0926
## 7 248187936265.1281 nan 0.0100 1379488118.2224
## 8 246721474161.0420 nan 0.0100 1475216648.5742
## 9 245242978301.7986 nan 0.0100 1491264084.5560
## 10 243784310206.4940 nan 0.0100 1610686005.4705
## 20 230700436683.9696 nan 0.0100 1256057887.8971
## 40 209576476479.5576 nan 0.0100 594522752.8332
## 60 193580104607.9822 nan 0.0100 713387829.7970
## 80 180986065432.4500 nan 0.0100 424728313.7643
## 100 170715202159.2541 nan 0.0100 502149903.2506
## 120 162076609825.1581 nan 0.0100 346175660.8611
## 140 154442140606.7857 nan 0.0100 323729763.1043
## 160 147821183744.1366 nan 0.0100 181340954.2634
## 180 141926214913.2726 nan 0.0100 195622063.4028
## 200 136567140523.2435 nan 0.0100 252125638.8107
## 220 131795030543.0642 nan 0.0100 238771660.0894
## 240 127425721579.6106 nan 0.0100 83390181.1519
## 260 123512121346.1268 nan 0.0100 151901651.7482
## 280 119995044437.6533 nan 0.0100 87735863.4599
## 300 116742988878.5492 nan 0.0100 158205025.5524
## 320 113828951583.5733 nan 0.0100 20070882.0999
## 340 111079593216.7477 nan 0.0100 92268209.8382
## 360 108558248233.5264 nan 0.0100 84431430.7344
## 380 106284826441.6808 nan 0.0100 105748693.6663
## 400 104116671870.3234 nan 0.0100 42216244.5562
## 420 102086263160.9963 nan 0.0100 -21094845.6796
## 440 100213240990.5605 nan 0.0100 87306650.5900
## 460 98494722832.7862 nan 0.0100 -2858632.3385
## 480 96890047202.0322 nan 0.0100 82273583.1514
## 500 95372618863.3887 nan 0.0100 -37096512.1382
## 520 93927654476.2579 nan 0.0100 64663699.2944
## 540 92589056500.4943 nan 0.0100 62849017.7391
## 560 91359621347.6124 nan 0.0100 63964051.0809
## 580 90220304519.3942 nan 0.0100 52678866.2058
## 600 89176770775.8266 nan 0.0100 29513658.3996
## 620 88199441917.3704 nan 0.0100 20535121.6932
## 640 87241259045.1935 nan 0.0100 40489257.1162
## 660 86354775659.2798 nan 0.0100 38228406.9883
## 680 85539052348.0791 nan 0.0100 37305480.0410
## 700 84774509967.1865 nan 0.0100 -4812938.4811
## 720 84055574489.9095 nan 0.0100 34206391.0470
## 740 83368708316.9685 nan 0.0100 23920943.1913
## 760 82737951448.6301 nan 0.0100 -3457051.1923
## 780 82108280779.3513 nan 0.0100 -2757149.5830
## 800 81518165926.0019 nan 0.0100 26883612.0775
## 820 80978010483.7325 nan 0.0100 -15450997.1695
## 840 80499287695.7616 nan 0.0100 12201282.9606
## 860 80037463346.2462 nan 0.0100 2796961.1555
## 880 79597451163.8670 nan 0.0100 -36397574.8719
## 900 79164725814.6078 nan 0.0100 13341556.9801
## 920 78761623398.7746 nan 0.0100 14745577.0155
## 940 78387933834.5166 nan 0.0100 1174052.1934
## 960 78042904779.0190 nan 0.0100 15886151.2971
## 980 77723292079.7293 nan 0.0100 4688807.4705
## 1000 77397181359.2678 nan 0.0100 7103754.0988
## 1020 77084637674.9434 nan 0.0100 -45492053.5692
## 1040 76819646576.3564 nan 0.0100 11845331.1130
## 1060 76540149530.0088 nan 0.0100 8910730.3510
## 1080 76283880694.7530 nan 0.0100 11358493.9373
## 1100 76038345422.5329 nan 0.0100 12255627.9154
## 1120 75794505938.8047 nan 0.0100 9911370.5666
## 1140 75572942168.5802 nan 0.0100 -7655752.1573
## 1160 75340211820.5780 nan 0.0100 8212626.9640
## 1180 75132225228.4569 nan 0.0100 -25716417.4434
## 1200 74943322829.9607 nan 0.0100 7115499.6816
## 1220 74765063018.0025 nan 0.0100 6846798.3590
## 1240 74600585777.9073 nan 0.0100 -11654787.0960
## 1260 74439315948.3663 nan 0.0100 -22918082.8731
## 1280 74257888046.8752 nan 0.0100 -18315141.7908
## 1300 74087971215.4799 nan 0.0100 -4228541.7056
## 1320 73941338115.5271 nan 0.0100 4601296.6164
## 1340 73780609799.3551 nan 0.0100 3294330.6447
## 1360 73631291941.2535 nan 0.0100 4889357.7534
## 1380 73486895148.6830 nan 0.0100 5869418.6255
## 1400 73376157259.4409 nan 0.0100 -25128705.9950
## 1420 73238500036.0696 nan 0.0100 -6236718.7715
## 1440 73114467307.4799 nan 0.0100 -19429714.9792
## 1460 73016811821.0501 nan 0.0100 -10956950.4528
## 1480 72896804690.7124 nan 0.0100 736092.1602
## 1500 72796749627.3175 nan 0.0100 -14483327.5855
## 1520 72677552049.8824 nan 0.0100 -27449551.6806
## 1540 72584460443.0135 nan 0.0100 -6187746.3726
## 1560 72471471819.7434 nan 0.0100 3517156.6772
## 1580 72376694044.9311 nan 0.0100 5430385.9739
## 1600 72275051989.2531 nan 0.0100 -16673047.3514
## 1620 72184162062.7276 nan 0.0100 -15121337.6874
## 1640 72088693139.9800 nan 0.0100 -3983019.9540
## 1660 71989325155.2247 nan 0.0100 1682163.7016
## 1680 71907663417.8677 nan 0.0100 4657172.4542
## 1700 71814750930.4284 nan 0.0100 3013925.5944
## 1720 71730893277.7537 nan 0.0100 4173734.0357
## 1740 71663223367.7475 nan 0.0100 2330142.5590
## 1760 71579925069.8628 nan 0.0100 -13974038.9772
## 1780 71490784387.2483 nan 0.0100 -16318556.5486
## 1800 71418546803.4612 nan 0.0100 -22409144.4918
## 1820 71349005676.8734 nan 0.0100 -14540905.4976
## 1840 71272287372.7785 nan 0.0100 -17615249.5088
## 1860 71209812893.5546 nan 0.0100 -27882235.1710
## 1880 71138263733.4566 nan 0.0100 -33012107.1969
## 1900 71066996124.2908 nan 0.0100 -7934291.8570
## 1920 71008960892.3363 nan 0.0100 1777113.5359
## 1940 70951506274.8544 nan 0.0100 -7552941.7812
## 1960 70881476842.0539 nan 0.0100 2011467.1098
## 1980 70812675321.8422 nan 0.0100 -5565252.5299
## 2000 70751827494.9715 nan 0.0100 3137612.1771
## 2020 70684732059.5374 nan 0.0100 2163229.9468
## 2040 70629385498.6061 nan 0.0100 -25180665.7648
## 2060 70566403093.5845 nan 0.0100 -19022329.9641
## 2080 70515588071.1683 nan 0.0100 -16334650.9005
## 2100 70467475808.3121 nan 0.0100 -12776242.0250
## 2120 70406513766.7574 nan 0.0100 -3709737.3478
## 2140 70357036492.0808 nan 0.0100 2238885.3487
## 2160 70306292208.9204 nan 0.0100 -4862421.4964
## 2180 70247301340.5489 nan 0.0100 2120497.2461
## 2200 70186663200.8844 nan 0.0100 -51372255.6010
## 2220 70134599216.4026 nan 0.0100 -6786207.2763
## 2240 70075091041.3860 nan 0.0100 -26353734.9117
## 2260 70030235536.5933 nan 0.0100 -8260202.4913
## 2280 69981964135.0658 nan 0.0100 -56742195.6793
## 2300 69926546089.6460 nan 0.0100 926030.5787
## 2320 69869497929.4693 nan 0.0100 2044873.1527
## 2340 69815770863.3722 nan 0.0100 1828261.1961
## 2360 69770467631.5173 nan 0.0100 849432.5904
## 2380 69718593408.4682 nan 0.0100 -14450022.4840
## 2400 69661820591.7697 nan 0.0100 -9962237.9748
## 2420 69615075362.4414 nan 0.0100 1350179.8809
## 2440 69577451554.5970 nan 0.0100 676307.8614
## 2460 69538483944.8005 nan 0.0100 -18093548.1750
## 2480 69488062921.4774 nan 0.0100 424957.3002
## 2500 69446459368.4350 nan 0.0100 -8844452.6789
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 256601830952.9774 nan 0.0100 2318887854.6975
## 2 254258681045.8215 nan 0.0100 2942333391.6349
## 3 251658755646.9848 nan 0.0100 2526985517.6759
## 4 249174949662.0016 nan 0.0100 1946431358.7589
## 5 246624590088.6355 nan 0.0100 2241382022.0566
## 6 244150311768.6161 nan 0.0100 1661408589.3026
## 7 241721539776.7988 nan 0.0100 2008644616.4271
## 8 239482605148.7787 nan 0.0100 2888270881.0484
## 9 237084966644.0344 nan 0.0100 1988326556.5691
## 10 234763181654.5068 nan 0.0100 2614308731.6209
## 20 213853588127.9988 nan 0.0100 2266968268.3403
## 40 180573934093.5429 nan 0.0100 1443188710.0702
## 60 156343612825.1929 nan 0.0100 1153872529.9244
## 80 137604110922.5337 nan 0.0100 651476324.1982
## 100 122572838484.2954 nan 0.0100 583827570.7447
## 120 110662317356.6498 nan 0.0100 580897651.8799
## 140 100927723053.5626 nan 0.0100 388198007.2019
## 160 92610702950.0898 nan 0.0100 350500892.4497
## 180 85669206029.9955 nan 0.0100 278447005.4674
## 200 79616793426.6627 nan 0.0100 200587333.1911
## 220 74408977767.0576 nan 0.0100 147137613.7125
## 240 69725985942.7621 nan 0.0100 318656726.8360
## 260 65766395506.6717 nan 0.0100 87556758.4929
## 280 62240662244.1777 nan 0.0100 162967056.1401
## 300 59298964706.9219 nan 0.0100 91031652.4600
## 320 56813244382.2145 nan 0.0100 109438674.5478
## 340 54664224971.0238 nan 0.0100 125836320.6588
## 360 52671990353.5299 nan 0.0100 59500283.5359
## 380 51000567926.7262 nan 0.0100 -4400820.7769
## 400 49547998345.1045 nan 0.0100 75041312.7755
## 420 48247103822.3111 nan 0.0100 23604327.1639
## 440 47028844994.9122 nan 0.0100 83866925.3706
## 460 45977489277.6946 nan 0.0100 53552605.8621
## 480 45116418881.7387 nan 0.0100 18379674.1928
## 500 44334975480.8476 nan 0.0100 4282046.4539
## 520 43614948985.2702 nan 0.0100 869691.8600
## 540 42961546084.4598 nan 0.0100 -10146737.0735
## 560 42379455743.0528 nan 0.0100 -5258313.3098
## 580 41844748735.5634 nan 0.0100 6141122.8295
## 600 41353544520.4175 nan 0.0100 24622499.4298
## 620 40925896324.2409 nan 0.0100 10506171.2774
## 640 40512563362.1247 nan 0.0100 -8011745.8044
## 660 40128286227.7328 nan 0.0100 -2818033.2880
## 680 39781092193.5598 nan 0.0100 -5640572.8968
## 700 39457197365.2616 nan 0.0100 -6121148.3223
## 720 39158313609.4562 nan 0.0100 -26704421.5625
## 740 38864436171.1826 nan 0.0100 9275511.6921
## 760 38595824828.9124 nan 0.0100 -9703948.6026
## 780 38355959901.4125 nan 0.0100 -3451514.8417
## 800 38089002354.4340 nan 0.0100 1040785.4833
## 820 37839737703.5145 nan 0.0100 9423039.4713
## 840 37591633011.3101 nan 0.0100 -16726903.8557
## 860 37370399386.1189 nan 0.0100 -5205325.9083
## 880 37164119833.1768 nan 0.0100 8728383.4607
## 900 36964079859.0043 nan 0.0100 1026453.5379
## 920 36763993949.2348 nan 0.0100 -13990986.5413
## 940 36579518988.3554 nan 0.0100 -9431382.6367
## 960 36358962065.6240 nan 0.0100 -18228475.1890
## 980 36171626746.4887 nan 0.0100 -26293523.0636
## 1000 35981264785.6401 nan 0.0100 3052956.7468
## 1020 35811487040.7636 nan 0.0100 -5499316.1095
## 1040 35655387414.0545 nan 0.0100 5050795.1781
## 1060 35477286174.3512 nan 0.0100 -13763502.1863
## 1080 35314206258.3251 nan 0.0100 -37833377.7314
## 1100 35164056797.8247 nan 0.0100 -19591036.8359
## 1120 35026631224.1836 nan 0.0100 -1529053.2598
## 1140 34880692929.3983 nan 0.0100 3936297.2837
## 1160 34707274266.7341 nan 0.0100 -7170224.6666
## 1180 34555166916.6982 nan 0.0100 4969540.7017
## 1200 34411766737.7559 nan 0.0100 -5615816.1621
## 1220 34240482391.8599 nan 0.0100 -5118328.7649
## 1240 34099571317.7892 nan 0.0100 -10573496.7966
## 1260 33926994507.4682 nan 0.0100 1684390.7252
## 1280 33761120064.4693 nan 0.0100 1781094.7543
## 1300 33658513283.2285 nan 0.0100 -28049501.8224
## 1320 33493549771.5725 nan 0.0100 -24866658.6407
## 1340 33345478321.4654 nan 0.0100 -8943915.4418
## 1360 33194411514.0221 nan 0.0100 -5760465.8880
## 1380 33067988899.7786 nan 0.0100 1651116.9682
## 1400 32926473243.5085 nan 0.0100 -5717138.7531
## 1420 32782469936.3675 nan 0.0100 1493631.7282
## 1440 32663579329.9702 nan 0.0100 -8873158.2251
## 1460 32574994100.5216 nan 0.0100 -9123062.5846
## 1480 32452554669.1583 nan 0.0100 -4967433.6638
## 1500 32324769324.5158 nan 0.0100 -14778716.6928
## 1520 32208769464.6806 nan 0.0100 -8266752.5774
## 1540 32104631993.2589 nan 0.0100 -5418298.6663
## 1560 31996070669.1870 nan 0.0100 561783.4744
## 1580 31876798592.6978 nan 0.0100 3885391.6393
## 1600 31752115575.7644 nan 0.0100 -10882891.2051
## 1620 31641181731.5420 nan 0.0100 -15826490.0809
## 1640 31523882701.1060 nan 0.0100 -15455044.5546
## 1660 31393079402.2347 nan 0.0100 1490815.0421
## 1680 31294270908.9963 nan 0.0100 -614571.4229
## 1700 31194177282.3933 nan 0.0100 2514130.6688
## 1720 31088368783.1898 nan 0.0100 -10010290.1540
## 1740 30958698800.3368 nan 0.0100 114295.5822
## 1760 30874074830.7123 nan 0.0100 5582234.4577
## 1780 30782861722.7902 nan 0.0100 -13210881.7822
## 1800 30681516518.5101 nan 0.0100 -13717359.6356
## 1820 30578029036.0438 nan 0.0100 -7903455.0144
## 1840 30484696375.4797 nan 0.0100 463019.7239
## 1860 30392984474.0850 nan 0.0100 -3813669.4522
## 1880 30313218285.4602 nan 0.0100 -11602653.5926
## 1900 30221065758.5546 nan 0.0100 -8179746.9787
## 1920 30127852258.9930 nan 0.0100 -15803511.2619
## 1940 30046587465.0899 nan 0.0100 -6259874.7353
## 1960 29937615950.3639 nan 0.0100 -7610548.5627
## 1980 29850436309.8391 nan 0.0100 59592.6872
## 2000 29763815226.9303 nan 0.0100 -2306512.8036
## 2020 29672881890.8578 nan 0.0100 -11966410.6087
## 2040 29588286795.9003 nan 0.0100 -6684803.8247
## 2060 29508148125.4273 nan 0.0100 -6293162.8089
## 2080 29427122100.7030 nan 0.0100 -697139.7537
## 2100 29352296212.7363 nan 0.0100 -12455185.1839
## 2120 29270038160.5849 nan 0.0100 -15044997.0411
## 2140 29193876739.7443 nan 0.0100 -7969123.1507
## 2160 29123180281.5377 nan 0.0100 -7920910.7043
## 2180 29043867536.4833 nan 0.0100 -7443506.6562
## 2200 28938468156.8969 nan 0.0100 -18905073.4077
## 2220 28861555498.3226 nan 0.0100 -69357.7312
## 2240 28769101580.5975 nan 0.0100 -997004.9416
## 2260 28689297165.2928 nan 0.0100 1976660.6618
## 2280 28604019643.3068 nan 0.0100 -3773550.7587
## 2300 28534271148.1043 nan 0.0100 -8323553.7380
## 2320 28465305802.7952 nan 0.0100 -7873886.2021
## 2340 28373167529.7277 nan 0.0100 -1380084.4385
## 2360 28308268125.1843 nan 0.0100 -4647674.6858
## 2380 28241364271.2601 nan 0.0100 -9680882.8791
## 2400 28177823412.2012 nan 0.0100 -10665330.5364
## 2420 28097854385.4823 nan 0.0100 -3036800.9563
## 2440 28010876688.0938 nan 0.0100 -12121283.0753
## 2460 27930842689.0099 nan 0.0100 -5021966.6754
## 2480 27842301690.5604 nan 0.0100 -16192793.1067
## 2500 27774131201.4027 nan 0.0100 -3895965.1210
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 256190683397.5144 nan 0.0100 3349482664.3480
## 2 253042729205.6471 nan 0.0100 2565463665.2982
## 3 250088433990.0945 nan 0.0100 2537682910.0766
## 4 247332963204.9278 nan 0.0100 2942148423.6510
## 5 244486955776.2025 nan 0.0100 2531305392.9732
## 6 241669967208.8791 nan 0.0100 3062355225.7021
## 7 238957176993.3274 nan 0.0100 3095339631.8336
## 8 236330884904.4835 nan 0.0100 2729403084.8095
## 9 233633328439.2131 nan 0.0100 2132166959.5011
## 10 231097951698.7996 nan 0.0100 2385884152.3400
## 20 206995970462.5822 nan 0.0100 2457586741.5283
## 40 169449191188.1197 nan 0.0100 1637955596.3911
## 60 141926253833.9827 nan 0.0100 963749836.8120
## 80 120945403539.1209 nan 0.0100 797451543.3839
## 100 105417657744.7347 nan 0.0100 637390154.6787
## 120 92994034813.5945 nan 0.0100 365039341.2969
## 140 83111215978.4990 nan 0.0100 419980365.8495
## 160 75047920042.5569 nan 0.0100 322901342.6429
## 180 68535377719.3759 nan 0.0100 214905769.3481
## 200 63243609654.6033 nan 0.0100 140195373.8269
## 220 58881145360.0675 nan 0.0100 137785908.4562
## 240 55170410214.9303 nan 0.0100 130284909.8359
## 260 52088548717.7493 nan 0.0100 131508396.5090
## 280 49566504300.1278 nan 0.0100 64052818.3608
## 300 47390674294.2980 nan 0.0100 89420801.1430
## 320 45550028629.2858 nan 0.0100 36194807.9022
## 340 43971988627.9382 nan 0.0100 27240614.3772
## 360 42612637039.0247 nan 0.0100 37274509.8319
## 380 41443184880.0584 nan 0.0100 26500221.5907
## 400 40433021952.2102 nan 0.0100 65340195.4559
## 420 39547789811.6306 nan 0.0100 11973296.4498
## 440 38745357051.4119 nan 0.0100 13526658.9079
## 460 38043375873.7262 nan 0.0100 8499325.4042
## 480 37433064404.7177 nan 0.0100 3722355.8781
## 500 36843302342.0948 nan 0.0100 13945174.5017
## 520 36321197998.0385 nan 0.0100 -2529828.5949
## 540 35883183003.0853 nan 0.0100 -3768047.8034
## 560 35455840459.7312 nan 0.0100 14388204.2148
## 580 34984288948.3086 nan 0.0100 14200400.8191
## 600 34658587461.7479 nan 0.0100 5482704.1741
## 620 34284533583.4349 nan 0.0100 -6230421.1043
## 640 33956441832.2161 nan 0.0100 -5711734.0814
## 660 33606503352.3273 nan 0.0100 -4485350.8416
## 680 33306986278.2889 nan 0.0100 -18800788.2584
## 700 33019602180.6018 nan 0.0100 -14433155.6788
## 720 32687139962.6555 nan 0.0100 -20116828.1173
## 740 32376905739.1459 nan 0.0100 -6360170.0141
## 760 32099458146.4178 nan 0.0100 -19900630.1997
## 780 31804304730.5051 nan 0.0100 -23100787.5375
## 800 31552389273.3419 nan 0.0100 -16391178.4930
## 820 31314119324.4610 nan 0.0100 -4300116.0410
## 840 31089959339.8989 nan 0.0100 6767651.1604
## 860 30857796497.2682 nan 0.0100 -29080342.8246
## 880 30617733653.9718 nan 0.0100 -14726926.3857
## 900 30404860037.5112 nan 0.0100 -11235742.1781
## 920 30177707583.7989 nan 0.0100 -16120198.1785
## 940 30006904924.9735 nan 0.0100 -11354758.1667
## 960 29800981281.3459 nan 0.0100 1544729.6568
## 980 29593409588.2458 nan 0.0100 -10817382.0991
## 1000 29383583951.5926 nan 0.0100 4328747.7350
## 1020 29188151900.0638 nan 0.0100 -21529180.4953
## 1040 29019750465.5546 nan 0.0100 -876245.7760
## 1060 28855445076.6023 nan 0.0100 -13912280.0760
## 1080 28669055497.4665 nan 0.0100 -3030719.9955
## 1100 28500828441.3449 nan 0.0100 -13304917.3534
## 1120 28325993989.6356 nan 0.0100 -2217119.4574
## 1140 28166556840.1064 nan 0.0100 -3696111.9367
## 1160 27973083376.8493 nan 0.0100 -7653009.0704
## 1180 27804601580.8554 nan 0.0100 1850002.9544
## 1200 27648927249.2059 nan 0.0100 -5959352.7161
## 1220 27470874760.2030 nan 0.0100 -4137627.8818
## 1240 27319813472.6187 nan 0.0100 286327.4673
## 1260 27152198146.8986 nan 0.0100 -436317.3516
## 1280 26998782621.1932 nan 0.0100 -10447222.7286
## 1300 26855624803.8620 nan 0.0100 3364981.3897
## 1320 26703049550.7212 nan 0.0100 -4064053.0823
## 1340 26549428317.6196 nan 0.0100 -12901335.7957
## 1360 26407859234.3449 nan 0.0100 2311227.0961
## 1380 26278957660.7703 nan 0.0100 -18441861.2730
## 1400 26166470878.0485 nan 0.0100 -3640537.8119
## 1420 26026381534.0570 nan 0.0100 650601.7431
## 1440 25882264376.3059 nan 0.0100 -8678393.2739
## 1460 25739231024.9968 nan 0.0100 -5675817.6237
## 1480 25623835064.8090 nan 0.0100 2371053.9368
## 1500 25493655248.6944 nan 0.0100 -5977500.1989
## 1520 25351380627.6615 nan 0.0100 31352.5269
## 1540 25222991957.4860 nan 0.0100 -5592790.0723
## 1560 25112178944.6052 nan 0.0100 -19793594.1321
## 1580 24971623519.0189 nan 0.0100 -10250085.9158
## 1600 24851159331.9399 nan 0.0100 180703.9505
## 1620 24744059441.1163 nan 0.0100 -5668700.5197
## 1640 24643578200.5427 nan 0.0100 -2920292.4699
## 1660 24533740649.0488 nan 0.0100 -3578614.8440
## 1680 24424842594.0923 nan 0.0100 -6899512.7063
## 1700 24286784297.6390 nan 0.0100 -4124953.6234
## 1720 24164578177.2500 nan 0.0100 -6543420.2247
## 1740 24062200601.8835 nan 0.0100 -5681074.5622
## 1760 23937873327.9331 nan 0.0100 -5579603.8839
## 1780 23822378665.6102 nan 0.0100 -7737477.7184
## 1800 23726260359.0052 nan 0.0100 -10560633.8220
## 1820 23635918149.4807 nan 0.0100 387199.9971
## 1840 23533958191.2970 nan 0.0100 -3581881.3475
## 1860 23428083292.5122 nan 0.0100 36660.5512
## 1880 23335691824.8283 nan 0.0100 -16821458.8457
## 1900 23241104218.3817 nan 0.0100 -4518677.4772
## 1920 23138784126.4688 nan 0.0100 -2112608.1224
## 1940 23026984897.9470 nan 0.0100 -1109.7293
## 1960 22950168807.1345 nan 0.0100 -17392466.6874
## 1980 22853117172.6169 nan 0.0100 -11637537.8382
## 2000 22762310280.4980 nan 0.0100 -11650015.1345
## 2020 22672848893.1460 nan 0.0100 -9386059.4423
## 2040 22591386063.5339 nan 0.0100 -970673.7678
## 2060 22488260957.2718 nan 0.0100 -11429857.5582
## 2080 22402252485.6193 nan 0.0100 -5680295.0249
## 2100 22314134351.6952 nan 0.0100 -5616062.3809
## 2120 22227108007.1104 nan 0.0100 -9064607.8821
## 2140 22135810006.1184 nan 0.0100 -4919766.3282
## 2160 22056770099.5256 nan 0.0100 198815.2526
## 2180 21973310395.0474 nan 0.0100 -2314017.9318
## 2200 21902250110.7528 nan 0.0100 -5456963.7713
## 2220 21827464807.5805 nan 0.0100 -6149684.4503
## 2240 21744186592.3950 nan 0.0100 68935.0532
## 2260 21664264652.8153 nan 0.0100 -3727782.4037
## 2280 21596858147.5985 nan 0.0100 -3953009.6942
## 2300 21520289505.7464 nan 0.0100 -11558888.3065
## 2320 21431978418.0920 nan 0.0100 -202706.4666
## 2340 21352052947.0312 nan 0.0100 -3522481.9915
## 2360 21272999441.7956 nan 0.0100 -529909.1859
## 2380 21196029806.4485 nan 0.0100 -3318551.9249
## 2400 21112328633.0727 nan 0.0100 -3814263.7217
## 2420 21051678664.1138 nan 0.0100 -6279646.7925
## 2440 20977839969.7501 nan 0.0100 -4716755.3269
## 2460 20893420874.2826 nan 0.0100 -4689279.4997
## 2480 20820491250.1365 nan 0.0100 -13318971.2851
## 2500 20747203040.7737 nan 0.0100 -14508060.9160
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 260034222881.2054 nan 0.0010 170706731.4075
## 2 259867616895.9361 nan 0.0010 146102842.5943
## 3 259702572669.3900 nan 0.0010 150152181.0917
## 4 259536569804.0539 nan 0.0010 125533248.6157
## 5 259374931920.4284 nan 0.0010 172522135.4484
## 6 259215622800.9181 nan 0.0010 137534535.1967
## 7 259060208998.8295 nan 0.0010 169306097.3722
## 8 258902068771.4586 nan 0.0010 161763323.0739
## 9 258725615520.9174 nan 0.0010 120190095.9197
## 10 258563726640.8978 nan 0.0010 157856206.7109
## 20 256973093322.6393 nan 0.0010 151324769.0141
## 40 253908887959.9503 nan 0.0010 149090688.6808
## 60 250939905132.9117 nan 0.0010 143411328.2940
## 80 248016136665.8043 nan 0.0010 129828248.5355
## 100 245179382629.4807 nan 0.0010 134939023.0939
## 120 242481100264.5319 nan 0.0010 145264843.3566
## 140 239834569584.9373 nan 0.0010 131371208.0184
## 160 237237219806.1421 nan 0.0010 128921618.9566
## 180 234725762237.5099 nan 0.0010 66509852.4028
## 200 232306913917.4705 nan 0.0010 111863505.3066
## 220 229956411469.8706 nan 0.0010 112961060.3338
## 240 227683636362.6516 nan 0.0010 86600328.5699
## 260 225469745128.5261 nan 0.0010 115603417.3799
## 280 223294259489.4256 nan 0.0010 87847273.7815
## 300 221202628474.7576 nan 0.0010 102652128.6028
## 320 219143863039.4036 nan 0.0010 89287851.0363
## 340 217148381065.1376 nan 0.0010 79768943.7634
## 360 215226106620.0028 nan 0.0010 76919855.2303
## 380 213366104338.5609 nan 0.0010 99573075.9635
## 400 211562618586.3143 nan 0.0010 91428639.5971
## 420 209781859541.1016 nan 0.0010 74591431.6577
## 440 208042404742.3675 nan 0.0010 84997855.9470
## 460 206360500849.3573 nan 0.0010 67233612.5601
## 480 204735184588.5654 nan 0.0010 83700434.7804
## 500 203125207318.2379 nan 0.0010 71349176.0098
## 520 201555658443.4899 nan 0.0010 62154590.7382
## 540 200039281828.3367 nan 0.0010 72012374.8800
## 560 198547254331.3811 nan 0.0010 52739995.2905
## 580 197131208480.3021 nan 0.0010 74232243.5575
## 600 195732651555.6994 nan 0.0010 57111323.3671
## 620 194369747776.2253 nan 0.0010 55144212.6969
## 640 193033437530.7079 nan 0.0010 52332048.4461
## 660 191733093656.9554 nan 0.0010 55919350.6339
## 680 190465144727.1203 nan 0.0010 62254105.2350
## 700 189240177123.7992 nan 0.0010 43847165.2994
## 720 188032424703.6071 nan 0.0010 56218377.7878
## 740 186855786812.5383 nan 0.0010 59405338.1808
## 760 185719560870.0959 nan 0.0010 52901033.6306
## 780 184609609838.7962 nan 0.0010 53947357.7841
## 800 183537286029.3469 nan 0.0010 35133439.2776
## 820 182483995622.4814 nan 0.0010 51754017.2984
## 840 181428556787.5975 nan 0.0010 36589080.9926
## 860 180412516840.9728 nan 0.0010 21464796.7315
## 880 179430024137.9696 nan 0.0010 38973892.5384
## 900 178452263699.7608 nan 0.0010 46632112.2124
## 920 177483867629.4080 nan 0.0010 50199368.8382
## 940 176542023670.0005 nan 0.0010 47343220.5506
## 960 175614443026.6907 nan 0.0010 42107945.3028
## 980 174704931422.2956 nan 0.0010 29539275.4911
## 1000 173818409449.8778 nan 0.0010 29080576.8276
## 1020 172928696240.1861 nan 0.0010 35993812.2598
## 1040 172060721711.2196 nan 0.0010 30893592.3697
## 1060 171207016199.4485 nan 0.0010 32896493.2967
## 1080 170356597417.5907 nan 0.0010 36524249.7145
## 1100 169523966475.6212 nan 0.0010 34839084.7412
## 1120 168696340766.3065 nan 0.0010 35387805.2382
## 1140 167883292769.2725 nan 0.0010 35786013.2199
## 1160 167089682265.2834 nan 0.0010 31122870.3739
## 1180 166312573811.4081 nan 0.0010 29391731.8183
## 1200 165542857771.4069 nan 0.0010 28527284.8922
## 1220 164768016613.4372 nan 0.0010 27535969.9933
## 1240 163995816493.5399 nan 0.0010 28397504.4427
## 1260 163245119110.3175 nan 0.0010 41045310.1700
## 1280 162513775236.4196 nan 0.0010 38667823.2868
## 1300 161786384149.9946 nan 0.0010 33596033.2409
## 1320 161062050083.3391 nan 0.0010 28502039.7728
## 1340 160347055346.1466 nan 0.0010 37921572.7976
## 1360 159626216784.7761 nan 0.0010 26555519.1720
## 1380 158932998221.9263 nan 0.0010 31907715.7580
## 1400 158246013865.8221 nan 0.0010 14176079.5638
## 1420 157565999524.4007 nan 0.0010 31288176.9848
## 1440 156891634971.0862 nan 0.0010 35255079.9407
## 1460 156210234252.8442 nan 0.0010 31355189.4533
## 1480 155550978213.4989 nan 0.0010 31194097.2266
## 1500 154889956927.2580 nan 0.0010 23343300.3484
## 1520 154237783689.2538 nan 0.0010 28397121.6024
## 1540 153594817330.7507 nan 0.0010 32010078.3829
## 1560 152965658253.8257 nan 0.0010 19196620.7362
## 1580 152336134669.2166 nan 0.0010 27660693.9853
## 1600 151727986731.3155 nan 0.0010 32841465.5737
## 1620 151116061624.4970 nan 0.0010 30444817.8799
## 1640 150504028320.4686 nan 0.0010 7599032.3475
## 1660 149905154013.5774 nan 0.0010 28160957.8321
## 1680 149319857397.9189 nan 0.0010 19211622.0947
## 1700 148722820988.0075 nan 0.0010 27633050.3434
## 1720 148145905093.9465 nan 0.0010 17248108.1175
## 1740 147572312057.2376 nan 0.0010 20643180.1564
## 1760 147004823313.1479 nan 0.0010 25746072.7359
## 1780 146445011071.7866 nan 0.0010 26478524.8923
## 1800 145892396848.7576 nan 0.0010 10783229.6011
## 1820 145338457469.4527 nan 0.0010 27415464.1636
## 1840 144794359413.0169 nan 0.0010 6200319.3421
## 1860 144258825546.5800 nan 0.0010 18116738.8717
## 1880 143721519697.5711 nan 0.0010 27221819.9642
## 1900 143188413767.5217 nan 0.0010 25635937.6942
## 1920 142658532119.0404 nan 0.0010 25447362.7862
## 1940 142133058803.5671 nan 0.0010 19286497.2157
## 1960 141645283351.9612 nan 0.0010 26049641.9157
## 1980 141138087359.6512 nan 0.0010 16447718.7583
## 2000 140642818815.3812 nan 0.0010 9026757.8063
## 2020 140153166503.7180 nan 0.0010 22425311.5870
## 2040 139662014727.3310 nan 0.0010 13962333.5525
## 2060 139174206859.8760 nan 0.0010 22352048.7521
## 2080 138686356003.6504 nan 0.0010 15648814.0495
## 2100 138204173722.2195 nan 0.0010 17371995.1356
## 2120 137734512292.7570 nan 0.0010 23428718.5224
## 2140 137275824458.2808 nan 0.0010 25423628.9126
## 2160 136806946383.9111 nan 0.0010 6956969.4096
## 2180 136348113824.5698 nan 0.0010 9455634.7371
## 2200 135905391984.2118 nan 0.0010 12274588.5334
## 2220 135457910239.3926 nan 0.0010 17474353.1438
## 2240 135016109027.9876 nan 0.0010 12158901.6285
## 2260 134575721800.0432 nan 0.0010 20580127.6171
## 2280 134140143130.7460 nan 0.0010 5778742.1138
## 2300 133714178260.7655 nan 0.0010 16274234.0706
## 2320 133292472818.8182 nan 0.0010 -2571985.5214
## 2340 132880743078.4554 nan 0.0010 10665492.3150
## 2360 132462169514.0269 nan 0.0010 13158060.2598
## 2380 132049113366.7635 nan 0.0010 10542837.6261
## 2400 131642372236.6938 nan 0.0010 17612738.7761
## 2420 131246033322.5789 nan 0.0010 2176168.6903
## 2440 130857733767.7497 nan 0.0010 9178920.2319
## 2460 130458828003.9840 nan 0.0010 19606192.6621
## 2480 130065724092.8688 nan 0.0010 -1288351.8916
## 2500 129684660066.8939 nan 0.0010 2543487.3339
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 259937526980.0036 nan 0.0010 301569295.5945
## 2 259676343455.6219 nan 0.0010 287952048.7761
## 3 259423862285.0798 nan 0.0010 254941332.9921
## 4 259162498738.2893 nan 0.0010 274577795.6666
## 5 258905516747.8099 nan 0.0010 282458866.9999
## 6 258637304856.3104 nan 0.0010 252169575.5316
## 7 258362730557.0481 nan 0.0010 250293831.1200
## 8 258094889275.3407 nan 0.0010 193291223.2347
## 9 257839807452.9778 nan 0.0010 279781346.6658
## 10 257589244662.7309 nan 0.0010 229707612.2991
## 20 254999518578.7948 nan 0.0010 205605089.6990
## 40 249911622024.0930 nan 0.0010 278669520.2561
## 60 245025764036.3871 nan 0.0010 197102763.2735
## 80 240253354613.5973 nan 0.0010 262919011.5331
## 100 235679545207.6034 nan 0.0010 252162576.4277
## 120 231219472204.6108 nan 0.0010 237099199.8264
## 140 226991066882.2349 nan 0.0010 171928041.5711
## 160 222893515372.7386 nan 0.0010 240397347.1219
## 180 218853532054.2567 nan 0.0010 175764265.4695
## 200 214985184528.0425 nan 0.0010 207960519.9543
## 220 211227287207.6988 nan 0.0010 190063257.3295
## 240 207587590555.8101 nan 0.0010 159403532.8074
## 260 204044646698.3097 nan 0.0010 165443261.1002
## 280 200581166556.9840 nan 0.0010 142448474.7413
## 300 197237661115.7822 nan 0.0010 153224471.5048
## 320 193981013933.4595 nan 0.0010 169220816.6902
## 340 190886584263.7844 nan 0.0010 110252847.6267
## 360 187859832188.2167 nan 0.0010 123773217.9305
## 380 184939846161.7734 nan 0.0010 130282645.1544
## 400 182097852380.4439 nan 0.0010 142547833.9951
## 420 179351690942.2086 nan 0.0010 125429442.0465
## 440 176642946290.7053 nan 0.0010 104998802.9445
## 460 174016171538.9073 nan 0.0010 104972938.6704
## 480 171483459766.4646 nan 0.0010 122446117.1405
## 500 169032673878.1160 nan 0.0010 118454941.0525
## 520 166643434479.1640 nan 0.0010 119741122.6786
## 540 164340862529.8134 nan 0.0010 67679486.1058
## 560 162103479542.9435 nan 0.0010 109966131.5182
## 580 159904121834.4275 nan 0.0010 91437747.0834
## 600 157757966768.0747 nan 0.0010 83807429.2488
## 620 155668764832.9441 nan 0.0010 104376221.7699
## 640 153648250067.9874 nan 0.0010 86683565.0808
## 660 151686090321.7233 nan 0.0010 104000655.3153
## 680 149765571476.4261 nan 0.0010 96439784.4275
## 700 147885131448.7464 nan 0.0010 67218267.6284
## 720 146078312336.0454 nan 0.0010 77595431.4889
## 740 144311668043.3097 nan 0.0010 79772012.7384
## 760 142576569951.2749 nan 0.0010 82548476.5155
## 780 140879923903.4901 nan 0.0010 77241082.1922
## 800 139234195824.9069 nan 0.0010 80393809.8168
## 820 137643859467.2202 nan 0.0010 91764710.8782
## 840 136060601981.8976 nan 0.0010 80547259.8259
## 860 134489353297.9032 nan 0.0010 57853412.8138
## 880 132976167076.0063 nan 0.0010 44421215.7938
## 900 131517912255.9365 nan 0.0010 71244812.6138
## 920 130103125215.2233 nan 0.0010 53674641.2154
## 940 128695984030.1708 nan 0.0010 33723007.2152
## 960 127331236815.9109 nan 0.0010 42279877.8915
## 980 125978878950.9865 nan 0.0010 75279577.3769
## 1000 124671165138.7542 nan 0.0010 57458505.3701
## 1020 123397759827.8029 nan 0.0010 53422749.8896
## 1040 122145836217.4099 nan 0.0010 50688651.2131
## 1060 120930595977.5110 nan 0.0010 61348652.0019
## 1080 119731418489.1634 nan 0.0010 47696460.5302
## 1100 118556311551.7121 nan 0.0010 36384259.2967
## 1120 117426680952.6761 nan 0.0010 58030703.6266
## 1140 116258598945.4366 nan 0.0010 54535433.7707
## 1160 115166379256.9466 nan 0.0010 44410584.0955
## 1180 114071374656.5567 nan 0.0010 38489732.2470
## 1200 113006579972.6293 nan 0.0010 36612328.5930
## 1220 111962057839.4171 nan 0.0010 43705483.9956
## 1240 110909373437.5701 nan 0.0010 47108924.3925
## 1260 109917968567.2533 nan 0.0010 28509443.7054
## 1280 108935053593.1530 nan 0.0010 53033535.6319
## 1300 107968415001.7910 nan 0.0010 39210849.2203
## 1320 106997785369.2995 nan 0.0010 29313913.0109
## 1340 106062472448.2091 nan 0.0010 39427866.5482
## 1360 105129514117.3958 nan 0.0010 35364191.8443
## 1380 104220530761.2616 nan 0.0010 26265324.2468
## 1400 103327373991.8752 nan 0.0010 31609899.5755
## 1420 102452928065.8099 nan 0.0010 28400889.2512
## 1440 101587405707.1070 nan 0.0010 35236657.6681
## 1460 100742302940.0237 nan 0.0010 23865601.0123
## 1480 99904657975.9706 nan 0.0010 39258236.6438
## 1500 99072119169.7837 nan 0.0010 36436865.4346
## 1520 98256555448.4012 nan 0.0010 39540745.1385
## 1540 97475212565.9034 nan 0.0010 42020100.2488
## 1560 96681585476.1344 nan 0.0010 22812334.9853
## 1580 95922429748.7974 nan 0.0010 35118813.7897
## 1600 95154605496.8232 nan 0.0010 39906471.6671
## 1620 94406067205.0724 nan 0.0010 22415612.2339
## 1640 93672468072.9624 nan 0.0010 29138208.7704
## 1660 92953223200.6523 nan 0.0010 31614166.8385
## 1680 92237094481.7783 nan 0.0010 21704714.3640
## 1700 91529689006.7377 nan 0.0010 30387913.3946
## 1720 90813203788.4134 nan 0.0010 39851755.4374
## 1740 90131273592.3854 nan 0.0010 28031385.4742
## 1760 89428066759.2807 nan 0.0010 27021056.5958
## 1780 88749211456.5845 nan 0.0010 47648177.9441
## 1800 88110581482.8145 nan 0.0010 23022684.5894
## 1820 87452538410.0727 nan 0.0010 28919400.7265
## 1840 86798602499.8770 nan 0.0010 21330573.6146
## 1860 86172605125.8201 nan 0.0010 27488751.8909
## 1880 85537931976.3995 nan 0.0010 27791307.9111
## 1900 84923207688.4327 nan 0.0010 23688117.6999
## 1920 84296796709.9381 nan 0.0010 30681909.3380
## 1940 83653014646.2954 nan 0.0010 33032079.6833
## 1960 83051834523.1947 nan 0.0010 24742407.5392
## 1980 82490151824.4396 nan 0.0010 18856788.3406
## 2000 81930403964.4676 nan 0.0010 9293483.3653
## 2020 81356267438.6207 nan 0.0010 7523889.2475
## 2040 80782584287.8327 nan 0.0010 22090125.8798
## 2060 80237361511.9930 nan 0.0010 16308862.5011
## 2080 79708594408.4948 nan 0.0010 12221643.0723
## 2100 79162920622.2455 nan 0.0010 34517709.2995
## 2120 78642376670.6640 nan 0.0010 21651971.8305
## 2140 78125239730.2524 nan 0.0010 15378340.7666
## 2160 77616927934.9012 nan 0.0010 14419394.4632
## 2180 77144880522.4924 nan 0.0010 9892215.7120
## 2200 76643632360.7488 nan 0.0010 16765254.8779
## 2220 76143679381.2009 nan 0.0010 29352633.8613
## 2240 75654185645.8682 nan 0.0010 18535450.7686
## 2260 75192483552.3333 nan 0.0010 28571932.5450
## 2280 74725848919.4607 nan 0.0010 20772105.3637
## 2300 74264512900.7398 nan 0.0010 19723992.9536
## 2320 73804683360.0227 nan 0.0010 21168210.3422
## 2340 73356342218.0012 nan 0.0010 23365579.9149
## 2360 72912405423.3973 nan 0.0010 10996719.5080
## 2380 72477353028.7001 nan 0.0010 14543192.4430
## 2400 72053243104.0088 nan 0.0010 11393853.8944
## 2420 71611070447.2485 nan 0.0010 34047816.9802
## 2440 71183504527.9193 nan 0.0010 14309794.2548
## 2460 70762802054.8344 nan 0.0010 10211811.0623
## 2480 70353008583.6388 nan 0.0010 9136216.3872
## 2500 69952389181.1811 nan 0.0010 2669556.6215
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 259902874377.0331 nan 0.0010 299012669.6899
## 2 259606468530.5122 nan 0.0010 289561848.3243
## 3 259296917807.5242 nan 0.0010 312683408.5218
## 4 259001293483.7339 nan 0.0010 323991544.1251
## 5 258686714389.4166 nan 0.0010 277687143.4864
## 6 258376490847.1401 nan 0.0010 327823151.9651
## 7 258092833599.0581 nan 0.0010 270689807.2761
## 8 257790369575.1613 nan 0.0010 260237632.7509
## 9 257487648524.2117 nan 0.0010 305118214.6456
## 10 257166528237.1778 nan 0.0010 245828048.7457
## 20 254210802436.6956 nan 0.0010 289433932.3454
## 40 248370110667.2466 nan 0.0010 255883840.9057
## 60 242767073069.9082 nan 0.0010 207149789.2820
## 80 237310518834.5941 nan 0.0010 276770883.1121
## 100 232080433653.0598 nan 0.0010 262518160.2438
## 120 226942425096.3813 nan 0.0010 279332574.0303
## 140 222076344890.7041 nan 0.0010 197350637.1560
## 160 217321040562.7082 nan 0.0010 243449964.4516
## 180 212765814199.4044 nan 0.0010 147882631.1491
## 200 208277086876.7812 nan 0.0010 224443975.4486
## 220 203979314095.6082 nan 0.0010 178333409.3688
## 240 199904919340.6800 nan 0.0010 200180217.9699
## 260 195903658977.9901 nan 0.0010 144932736.2317
## 280 192050083615.0844 nan 0.0010 176778002.4526
## 300 188278205061.6111 nan 0.0010 143262443.9335
## 320 184652217083.3683 nan 0.0010 188924016.0976
## 340 181108936029.2682 nan 0.0010 225936645.8491
## 360 177685956762.1469 nan 0.0010 122327542.5953
## 380 174326553159.2774 nan 0.0010 126548424.7734
## 400 171119451409.4123 nan 0.0010 137092815.3586
## 420 168000152616.0821 nan 0.0010 114965223.1319
## 440 164952426272.5832 nan 0.0010 111657010.4201
## 460 162034525828.3653 nan 0.0010 133832733.2835
## 480 159228059925.9088 nan 0.0010 136028834.0404
## 500 156452461405.8057 nan 0.0010 118254434.1572
## 520 153794306533.5807 nan 0.0010 96829743.7618
## 540 151192701301.9125 nan 0.0010 121488530.4633
## 560 148662233307.1590 nan 0.0010 97502128.4955
## 580 146179586757.3334 nan 0.0010 94038197.3407
## 600 143807106826.6334 nan 0.0010 127062583.2554
## 620 141491638217.3230 nan 0.0010 137485384.8488
## 640 139197917334.7122 nan 0.0010 98774334.9273
## 660 137017558337.2146 nan 0.0010 75672896.3232
## 680 134901280273.9696 nan 0.0010 73894234.8814
## 700 132850671382.8978 nan 0.0010 132120464.5670
## 720 130869057565.0622 nan 0.0010 60149830.1603
## 740 128919971289.7009 nan 0.0010 60493858.8121
## 760 127034975493.7696 nan 0.0010 75361104.3257
## 780 125215368997.2915 nan 0.0010 73894586.6888
## 800 123422463654.5727 nan 0.0010 50704428.3216
## 820 121680104498.6289 nan 0.0010 63180746.8404
## 840 119983375850.2956 nan 0.0010 51698336.2706
## 860 118343501446.3346 nan 0.0010 82132693.0163
## 880 116732762423.1676 nan 0.0010 73615502.1679
## 900 115195783639.6943 nan 0.0010 73775326.4580
## 920 113663037444.3910 nan 0.0010 67455613.3064
## 940 112162182760.0181 nan 0.0010 59486783.9909
## 960 110696567138.0808 nan 0.0010 66006076.2529
## 980 109291206549.9128 nan 0.0010 79420071.0032
## 1000 107894949955.7362 nan 0.0010 54535050.4893
## 1020 106550264569.0890 nan 0.0010 40356547.9426
## 1040 105243339934.7036 nan 0.0010 50192328.1599
## 1060 103944516944.9949 nan 0.0010 60737847.4643
## 1080 102678988867.4392 nan 0.0010 56437657.7622
## 1100 101440021278.3741 nan 0.0010 51606112.6721
## 1120 100243020697.9743 nan 0.0010 52221282.7621
## 1140 99060109695.3203 nan 0.0010 54290857.8139
## 1160 97917343866.8538 nan 0.0010 39100607.2037
## 1180 96807757941.9268 nan 0.0010 28914340.5269
## 1200 95701487348.2974 nan 0.0010 50483100.1065
## 1220 94621525417.8692 nan 0.0010 45432575.0574
## 1240 93564086822.8754 nan 0.0010 54276721.5624
## 1260 92506623076.7097 nan 0.0010 39051559.7772
## 1280 91485750371.2305 nan 0.0010 37104243.0329
## 1300 90503947088.9136 nan 0.0010 30680122.3012
## 1320 89522053160.1654 nan 0.0010 36100721.8979
## 1340 88580588924.8609 nan 0.0010 38139133.4272
## 1360 87640256006.4529 nan 0.0010 26081568.1637
## 1380 86709069314.1737 nan 0.0010 34345937.4900
## 1400 85813874976.7906 nan 0.0010 28289231.5282
## 1420 84949293981.6212 nan 0.0010 46675841.1372
## 1440 84097487978.0998 nan 0.0010 25057033.9867
## 1460 83260838495.0837 nan 0.0010 40013615.6060
## 1480 82430913720.0817 nan 0.0010 20654906.8384
## 1500 81619888948.6815 nan 0.0010 30032901.5702
## 1520 80838063392.6986 nan 0.0010 37892988.6251
## 1540 80061617114.0281 nan 0.0010 28330936.3544
## 1560 79278849597.5675 nan 0.0010 39731350.5879
## 1580 78545839208.6851 nan 0.0010 28075209.5150
## 1600 77831381083.9824 nan 0.0010 25435589.2174
## 1620 77123798951.7733 nan 0.0010 19364646.5713
## 1640 76429399669.7705 nan 0.0010 27488303.1014
## 1660 75732486237.7630 nan 0.0010 30250274.0568
## 1680 75057041859.0890 nan 0.0010 31826033.4225
## 1700 74405112457.1341 nan 0.0010 13805999.6880
## 1720 73763861636.1058 nan 0.0010 22571604.2555
## 1740 73126474787.0548 nan 0.0010 28745531.7296
## 1760 72512936323.6311 nan 0.0010 37876021.5514
## 1780 71888884914.0802 nan 0.0010 18349201.7038
## 1800 71284010598.7021 nan 0.0010 19752824.2457
## 1820 70693882884.7050 nan 0.0010 18868295.1024
## 1840 70104732567.2095 nan 0.0010 19802675.0757
## 1860 69522230325.1860 nan 0.0010 13822629.4731
## 1880 68960043940.6642 nan 0.0010 17952367.3804
## 1900 68420410562.3917 nan 0.0010 15717654.1386
## 1920 67873506056.6097 nan 0.0010 28395544.2653
## 1940 67339295520.9578 nan 0.0010 22664668.7061
## 1960 66831331779.0103 nan 0.0010 25163245.5237
## 1980 66318005012.7266 nan 0.0010 22670286.2512
## 2000 65818823508.7909 nan 0.0010 17237015.0937
## 2020 65322898527.9830 nan 0.0010 15692214.7751
## 2040 64832255090.8527 nan 0.0010 15361211.4261
## 2060 64352427015.2533 nan 0.0010 20669443.6095
## 2080 63890142683.9264 nan 0.0010 10257105.3376
## 2100 63434226368.1587 nan 0.0010 8947768.2001
## 2120 62991437996.8766 nan 0.0010 14831825.4329
## 2140 62551729641.3206 nan 0.0010 18325325.6639
## 2160 62112917459.4607 nan 0.0010 20498832.1087
## 2180 61690208729.1730 nan 0.0010 17895004.9275
## 2200 61251309286.2918 nan 0.0010 26842849.2805
## 2220 60841470654.5896 nan 0.0010 19980919.3005
## 2240 60446082965.7391 nan 0.0010 7334320.5671
## 2260 60051712048.6722 nan 0.0010 10133701.6203
## 2280 59663306403.0115 nan 0.0010 16346492.2248
## 2300 59279024692.5652 nan 0.0010 14031907.9030
## 2320 58902377193.2169 nan 0.0010 20384697.9414
## 2340 58518415127.5463 nan 0.0010 24233549.7771
## 2360 58156143345.1562 nan 0.0010 7131591.3438
## 2380 57783307133.4434 nan 0.0010 15798260.6579
## 2400 57423069215.3847 nan 0.0010 17329790.3583
## 2420 57079788713.8529 nan 0.0010 14727442.4369
## 2440 56736637574.3220 nan 0.0010 9724037.5163
## 2460 56409513589.2842 nan 0.0010 8928838.7290
## 2480 56077993765.7566 nan 0.0010 10294101.1329
## 2500 55752685193.4140 nan 0.0010 13024215.6377
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 258581004513.1557 nan 0.0100 1837690244.7243
## 2 257026399936.1899 nan 0.0100 1712382747.0442
## 3 255344023120.1605 nan 0.0100 1128197321.9741
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## 7 249459156205.2140 nan 0.0100 1579336118.1835
## 8 248017305986.3875 nan 0.0100 1448186646.4337
## 9 246518217258.8288 nan 0.0100 1056491169.7206
## 10 245121038520.2101 nan 0.0100 1310263963.4810
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## 60 195533027143.6770 nan 0.0100 518359401.0150
## 80 183311451756.7072 nan 0.0100 387690575.1821
## 100 173543223168.3198 nan 0.0100 269030514.1044
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## 140 158047076280.3792 nan 0.0100 355254256.6836
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## 340 115230808421.9628 nan 0.0100 43766482.5412
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## 600 93215819000.8645 nan 0.0100 56401195.8837
## 620 92228374746.0306 nan 0.0100 14964229.1944
## 640 91290787146.2229 nan 0.0100 46688174.2901
## 660 90406118584.9022 nan 0.0100 42564581.4668
## 680 89575096051.0234 nan 0.0100 -14269462.2342
## 700 88791342740.7860 nan 0.0100 -17470384.6824
## 720 88050503209.3713 nan 0.0100 35988525.7884
## 740 87364770386.6980 nan 0.0100 -14809383.2876
## 760 86720707923.5115 nan 0.0100 23022446.9449
## 780 86117547178.1609 nan 0.0100 27325523.8808
## 800 85565857527.7392 nan 0.0100 25029101.3131
## 820 85031577890.5663 nan 0.0100 25583865.4131
## 840 84533183415.4751 nan 0.0100 18143529.8407
## 860 84069975519.8245 nan 0.0100 104753.0712
## 880 83631951154.7057 nan 0.0100 23910115.2105
## 900 83207570959.0968 nan 0.0100 16890175.0377
## 920 82806044578.1322 nan 0.0100 -21783356.1695
## 940 82443657831.9834 nan 0.0100 17236976.7496
## 960 82115983501.9184 nan 0.0100 13295241.3087
## 980 81775284911.7411 nan 0.0100 13769196.4431
## 1000 81450977774.8783 nan 0.0100 15346877.6795
## 1020 81161550640.9532 nan 0.0100 -58243013.4254
## 1040 80869570106.3002 nan 0.0100 13729361.3945
## 1060 80604208997.3086 nan 0.0100 7477169.2156
## 1080 80345871807.7174 nan 0.0100 1691008.9593
## 1100 80100490022.9885 nan 0.0100 -24732658.0339
## 1120 79859398358.4525 nan 0.0100 8130445.5932
## 1140 79634677349.9349 nan 0.0100 -6983052.1254
## 1160 79423163496.9519 nan 0.0100 9942223.9786
## 1180 79220928603.2899 nan 0.0100 10237738.2500
## 1200 79060502916.0666 nan 0.0100 -33784283.6035
## 1220 78886830675.7707 nan 0.0100 7662935.2912
## 1240 78710027933.3224 nan 0.0100 5972110.9583
## 1260 78537629770.3176 nan 0.0100 -13199475.8177
## 1280 78384065053.2957 nan 0.0100 -38961394.7914
## 1300 78231295214.5921 nan 0.0100 2362098.7249
## 1320 78080572957.6070 nan 0.0100 7000512.1561
## 1340 77953888029.7670 nan 0.0100 -24221953.5728
## 1360 77807809234.5272 nan 0.0100 -381625.0794
## 1380 77667062699.4320 nan 0.0100 3329130.6360
## 1400 77543019330.9072 nan 0.0100 -64957539.8482
## 1420 77420128015.7686 nan 0.0100 -16418731.3332
## 1440 77317791602.1369 nan 0.0100 5592433.3816
## 1460 77212820773.1235 nan 0.0100 -12897017.2803
## 1480 77114484188.2369 nan 0.0100 -19116654.2832
## 1500 77029436436.1696 nan 0.0100 3943813.2040
## 1520 76927457116.6871 nan 0.0100 2707278.7009
## 1540 76830456252.9885 nan 0.0100 1754773.0795
## 1560 76758380735.0527 nan 0.0100 -42954513.1207
## 1580 76660129994.8235 nan 0.0100 1548431.7613
## 1600 76585360314.6113 nan 0.0100 -32062360.0851
## 1620 76495468386.8588 nan 0.0100 -28931756.6747
## 1640 76429549314.7758 nan 0.0100 -14542859.2513
## 1660 76363287762.4471 nan 0.0100 -39529548.0701
## 1680 76275192162.8805 nan 0.0100 -21655246.2114
## 1700 76197420926.1016 nan 0.0100 -20478592.2308
## 1720 76120890327.6699 nan 0.0100 -9369443.9173
## 1740 76037913823.0138 nan 0.0100 -8031171.8395
## 1760 75964073165.7509 nan 0.0100 -22394759.7534
## 1780 75892192673.0179 nan 0.0100 -48657826.8425
## 1800 75828627441.3446 nan 0.0100 -17259645.6280
## 1820 75753614643.0895 nan 0.0100 -14696679.0651
## 1840 75671290326.7201 nan 0.0100 -8303152.4835
## 1860 75595216581.0030 nan 0.0100 -9073225.6085
## 1880 75541427777.4210 nan 0.0100 253367.1467
## 1900 75476196416.8821 nan 0.0100 -12611726.1851
## 1920 75406979621.5291 nan 0.0100 -20948224.4664
## 1940 75333230446.0083 nan 0.0100 2953674.0693
## 1960 75256254490.2834 nan 0.0100 -8390472.0791
## 1980 75193507880.7626 nan 0.0100 -26500376.6221
## 2000 75120550134.1068 nan 0.0100 -13484118.6303
## 2020 75056699355.4520 nan 0.0100 -51741392.0003
## 2040 74995163231.5262 nan 0.0100 -7222622.2566
## 2060 74937347520.3535 nan 0.0100 -20231110.5869
## 2080 74876159764.3217 nan 0.0100 -909308.9247
## 2100 74820413688.9445 nan 0.0100 -44249657.8632
## 2120 74760483003.9314 nan 0.0100 -58135195.0690
## 2140 74703840597.0145 nan 0.0100 -6784979.8399
## 2160 74648268483.3686 nan 0.0100 2644465.4745
## 2180 74584997415.1738 nan 0.0100 -11016945.6318
## 2200 74527382562.2390 nan 0.0100 -38625803.7756
## 2220 74470640207.1515 nan 0.0100 -24354537.9113
## 2240 74425095334.0375 nan 0.0100 -41902723.9134
## 2260 74379478658.5790 nan 0.0100 -14027066.4267
## 2280 74331716757.0944 nan 0.0100 -7370135.1750
## 2300 74279388974.0877 nan 0.0100 -4767084.5600
## 2320 74225657970.6278 nan 0.0100 2425607.2868
## 2340 74172518199.7927 nan 0.0100 -26721053.0796
## 2360 74118380690.6755 nan 0.0100 -46080895.6015
## 2380 74061814770.3990 nan 0.0100 2352330.5734
## 2400 74008170080.0546 nan 0.0100 -3720279.8630
## 2420 73957371144.1678 nan 0.0100 1344247.3823
## 2440 73905927462.8948 nan 0.0100 -12341482.4574
## 2460 73861003192.8057 nan 0.0100 1217696.4901
## 2480 73805018664.2761 nan 0.0100 933213.5051
## 2500 73757746650.7504 nan 0.0100 -17679393.5974
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 257461794970.6996 nan 0.0100 2563577210.2846
## 2 254873992091.4185 nan 0.0100 3078688291.3617
## 3 252323425286.9560 nan 0.0100 2641361962.2523
## 4 249732721621.6621 nan 0.0100 1937449481.5474
## 5 247272526765.2367 nan 0.0100 2412391434.0043
## 6 244899480413.5423 nan 0.0100 2683891649.1998
## 7 242403963564.9720 nan 0.0100 2464283950.4280
## 8 240168341510.1081 nan 0.0100 2107922265.8916
## 9 237934327247.7156 nan 0.0100 1441220625.2510
## 10 235496045538.0056 nan 0.0100 1830027247.7004
## 20 214979112243.8560 nan 0.0100 2101380900.9163
## 40 182003353835.3220 nan 0.0100 1893823083.9718
## 60 157450251790.7215 nan 0.0100 930930560.1694
## 80 138853110021.6060 nan 0.0100 941162780.8831
## 100 124282283173.5000 nan 0.0100 462135106.0442
## 120 112664803667.0151 nan 0.0100 381987646.7385
## 140 103360114768.7663 nan 0.0100 356744625.8569
## 160 94927928925.9522 nan 0.0100 382684314.4083
## 180 87905619822.0455 nan 0.0100 241002667.5191
## 200 81846690678.7304 nan 0.0100 261749035.8113
## 220 76695671905.0577 nan 0.0100 10367567.5706
## 240 71962234509.6976 nan 0.0100 160579949.5697
## 260 68038172198.2331 nan 0.0100 111246602.0489
## 280 64681077002.9152 nan 0.0100 157313837.2561
## 300 61718290765.2661 nan 0.0100 86944404.7714
## 320 59139546089.7897 nan 0.0100 86637386.6838
## 340 56835641009.8517 nan 0.0100 78535677.4020
## 360 54935089122.0074 nan 0.0100 46239175.9456
## 380 53230851423.6450 nan 0.0100 28599623.6002
## 400 51788335901.7154 nan 0.0100 70570582.4045
## 420 50467582127.3165 nan 0.0100 33703535.2067
## 440 49275526362.7822 nan 0.0100 44945198.2586
## 460 48246393590.4765 nan 0.0100 34049905.2891
## 480 47312509383.9715 nan 0.0100 29770392.4562
## 500 46522889829.2871 nan 0.0100 36326034.5547
## 520 45745588463.1751 nan 0.0100 489607.5715
## 540 45062391861.7461 nan 0.0100 3247165.9570
## 560 44449352814.3543 nan 0.0100 -1420027.5377
## 580 43886092917.6014 nan 0.0100 -188275.5236
## 600 43357791549.2731 nan 0.0100 -1246767.8718
## 620 42928735673.7334 nan 0.0100 -24100951.5679
## 640 42461238595.5088 nan 0.0100 -321849.0593
## 660 42020666662.5130 nan 0.0100 4639004.0418
## 680 41603686454.5955 nan 0.0100 43628.8835
## 700 41293213381.7626 nan 0.0100 -61954472.1906
## 720 40930399005.0757 nan 0.0100 -3457119.4498
## 740 40608442533.3973 nan 0.0100 -8367148.8802
## 760 40285051594.6314 nan 0.0100 2038760.8838
## 780 39970473431.8022 nan 0.0100 -21800649.3025
## 800 39696481341.7512 nan 0.0100 -33072367.3680
## 820 39360565925.7028 nan 0.0100 11100408.1446
## 840 39106177510.5320 nan 0.0100 -19571027.1238
## 860 38834478951.9525 nan 0.0100 -8202163.8950
## 880 38550398693.4737 nan 0.0100 -41988516.8661
## 900 38291391823.6567 nan 0.0100 -20212700.8200
## 920 38072309873.7253 nan 0.0100 -2340525.9496
## 940 37816680629.6324 nan 0.0100 1162560.2449
## 960 37605326579.1941 nan 0.0100 -17536851.6993
## 980 37417148889.6085 nan 0.0100 -5993344.1151
## 1000 37226998714.4959 nan 0.0100 6700741.4622
## 1020 36973535719.8498 nan 0.0100 4555186.1451
## 1040 36782385426.9939 nan 0.0100 -201867.9115
## 1060 36593479662.5717 nan 0.0100 -3234008.7255
## 1080 36403507143.9298 nan 0.0100 -16668389.2030
## 1100 36238271226.3678 nan 0.0100 -8740955.9634
## 1120 36060115917.2154 nan 0.0100 -13679018.1168
## 1140 35879277261.8986 nan 0.0100 4617282.5777
## 1160 35714274501.1460 nan 0.0100 -22722625.2995
## 1180 35531900360.3863 nan 0.0100 -10824068.8291
## 1200 35370323047.2772 nan 0.0100 -10344695.8211
## 1220 35206936329.8737 nan 0.0100 9289118.4646
## 1240 35021831275.0730 nan 0.0100 -10254286.9154
## 1260 34854124729.7833 nan 0.0100 -4910072.0781
## 1280 34710095015.3239 nan 0.0100 -15660674.5092
## 1300 34584920185.5880 nan 0.0100 -12363681.4118
## 1320 34415540804.0222 nan 0.0100 -10429999.0290
## 1340 34262812298.3487 nan 0.0100 -8714338.3505
## 1360 34074718146.8858 nan 0.0100 -6693372.8528
## 1380 33923683290.6569 nan 0.0100 -53813394.0457
## 1400 33797097506.9349 nan 0.0100 2755851.1417
## 1420 33658317420.6705 nan 0.0100 -4162869.2060
## 1440 33499475450.7340 nan 0.0100 -19323133.7902
## 1460 33324221826.5593 nan 0.0100 594675.6758
## 1480 33162486320.6911 nan 0.0100 -11072684.5884
## 1500 33031155982.1045 nan 0.0100 -405366.5803
## 1520 32895235513.3161 nan 0.0100 -13274732.4366
## 1540 32753390367.8681 nan 0.0100 -10373521.9148
## 1560 32615525186.6314 nan 0.0100 -7839450.6195
## 1580 32488727927.8467 nan 0.0100 -4519186.0066
## 1600 32338546343.2902 nan 0.0100 -30323316.4795
## 1620 32203775359.1135 nan 0.0100 -23802038.1518
## 1640 32071032362.8436 nan 0.0100 -17581495.3528
## 1660 31941169367.1143 nan 0.0100 -8059744.0234
## 1680 31823289401.0881 nan 0.0100 -194833.6511
## 1700 31707571244.5230 nan 0.0100 -7954585.1874
## 1720 31572916990.9865 nan 0.0100 -10357768.6334
## 1740 31467955869.3002 nan 0.0100 -11232360.3006
## 1760 31347541737.6599 nan 0.0100 -3558794.8798
## 1780 31245987312.2955 nan 0.0100 -24414549.2235
## 1800 31128537119.8008 nan 0.0100 -4088853.4209
## 1820 31015571854.1824 nan 0.0100 -3265953.1374
## 1840 30885998184.1302 nan 0.0100 -14074259.3339
## 1860 30788796735.6351 nan 0.0100 -4717232.8684
## 1880 30688369687.7000 nan 0.0100 -20158678.9107
## 1900 30571471437.4104 nan 0.0100 7968997.2629
## 1920 30457542566.8005 nan 0.0100 -1471963.2004
## 1940 30371862799.3965 nan 0.0100 -8787040.1772
## 1960 30263847121.3036 nan 0.0100 -1370170.7571
## 1980 30138997892.7199 nan 0.0100 -9750072.6144
## 2000 30049629130.2159 nan 0.0100 -7356295.3744
## 2020 29948033480.3213 nan 0.0100 -28174165.6131
## 2040 29819971767.7363 nan 0.0100 -13014738.0976
## 2060 29728637604.3440 nan 0.0100 -8412552.5493
## 2080 29630140981.3861 nan 0.0100 -33299346.1981
## 2100 29536952181.8772 nan 0.0100 -23696106.1576
## 2120 29404275566.2443 nan 0.0100 -4913951.5703
## 2140 29302902836.4629 nan 0.0100 -23961288.2151
## 2160 29201059528.5379 nan 0.0100 -10872080.6361
## 2180 29126571130.1035 nan 0.0100 -14396488.2580
## 2200 29035205728.8573 nan 0.0100 1656059.7409
## 2220 28948536489.0274 nan 0.0100 -6848633.3453
## 2240 28858423818.9505 nan 0.0100 -12205895.2564
## 2260 28762628158.0946 nan 0.0100 2529125.5573
## 2280 28676978096.4335 nan 0.0100 -4741974.8582
## 2300 28601144990.6689 nan 0.0100 -7748476.9055
## 2320 28511269667.7600 nan 0.0100 -10868486.8715
## 2340 28424561557.0992 nan 0.0100 -886606.4479
## 2360 28351873351.0809 nan 0.0100 -6367894.4235
## 2380 28272715010.1763 nan 0.0100 681564.2764
## 2400 28178610288.0530 nan 0.0100 -7923097.3717
## 2420 28076585516.5494 nan 0.0100 -1791418.2681
## 2440 27992525181.0751 nan 0.0100 -5236176.0548
## 2460 27910909493.2371 nan 0.0100 -13030032.1614
## 2480 27845462070.1207 nan 0.0100 358938.6906
## 2500 27762238830.0268 nan 0.0100 -5747477.5461
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 257306641652.3129 nan 0.0100 3240817767.6787
## 2 254327472932.0212 nan 0.0100 3069747307.8813
## 3 251375770003.9824 nan 0.0100 2984448864.2850
## 4 248455767606.2266 nan 0.0100 2696974092.9532
## 5 245602960200.0310 nan 0.0100 2790636399.7622
## 6 242731020694.5450 nan 0.0100 3018108029.9992
## 7 239997766983.5893 nan 0.0100 2755466768.5577
## 8 237203902877.1554 nan 0.0100 1780812313.3625
## 9 234691506591.0064 nan 0.0100 2519343525.6905
## 10 232109803398.4683 nan 0.0100 2127325481.9246
## 20 208561149674.6909 nan 0.0100 1426434165.6473
## 40 171072778401.1814 nan 0.0100 1257696968.8669
## 60 143340666977.1878 nan 0.0100 758165855.3850
## 80 123122897040.2793 nan 0.0100 593306379.6594
## 100 107645955382.2840 nan 0.0100 576369798.5880
## 120 95445955593.0043 nan 0.0100 439615992.4616
## 140 85619041946.8960 nan 0.0100 429286505.0578
## 160 77488606238.8814 nan 0.0100 271048052.8801
## 180 70816135293.1942 nan 0.0100 233136188.7068
## 200 65524900559.0560 nan 0.0100 160804986.1453
## 220 61027011222.4903 nan 0.0100 155392129.9823
## 240 57230423942.4710 nan 0.0100 132000374.4498
## 260 53996126453.4855 nan 0.0100 118383365.1860
## 280 51277238163.3533 nan 0.0100 35184931.2793
## 300 48963219160.3141 nan 0.0100 56126095.0242
## 320 46977000496.0614 nan 0.0100 65153575.7375
## 340 45302138268.2263 nan 0.0100 51128182.5031
## 360 43858021979.2558 nan 0.0100 -18544772.6174
## 380 42601981581.0650 nan 0.0100 -26017071.0128
## 400 41497273084.1994 nan 0.0100 25136700.8854
## 420 40484511447.8426 nan 0.0100 26194391.2570
## 440 39546877036.1892 nan 0.0100 22581031.9520
## 460 38736253057.6545 nan 0.0100 -28345073.1733
## 480 38044275092.3593 nan 0.0100 9832874.0190
## 500 37421951620.6731 nan 0.0100 11092105.6814
## 520 36875633630.0094 nan 0.0100 -11321177.5600
## 540 36345593597.7206 nan 0.0100 -75490222.5769
## 560 35840287020.2531 nan 0.0100 11244883.0818
## 580 35373681657.3501 nan 0.0100 -10976024.1958
## 600 34942894659.6811 nan 0.0100 -17657032.2151
## 620 34491021853.7958 nan 0.0100 -382641.8090
## 640 34114751490.7648 nan 0.0100 -20226247.0797
## 660 33718846326.8833 nan 0.0100 1541852.4631
## 680 33361400777.6701 nan 0.0100 -17123258.6710
## 700 33044396432.6971 nan 0.0100 -1747425.6304
## 720 32743088087.7657 nan 0.0100 -16385389.4958
## 740 32401955731.5953 nan 0.0100 -5838047.3931
## 760 32115727112.5626 nan 0.0100 7616529.4272
## 780 31860180345.7733 nan 0.0100 -7861778.6786
## 800 31567866795.4991 nan 0.0100 11985.0897
## 820 31313706513.5770 nan 0.0100 4651958.5083
## 840 31023671479.2123 nan 0.0100 5921161.1706
## 860 30762781520.3095 nan 0.0100 -10907724.5105
## 880 30512342434.2007 nan 0.0100 -10274896.5298
## 900 30267218220.5835 nan 0.0100 -13032101.4920
## 920 30023037401.1116 nan 0.0100 -8559886.8286
## 940 29806795722.1431 nan 0.0100 -7320282.1073
## 960 29550278551.8891 nan 0.0100 -10470434.5865
## 980 29345944644.1159 nan 0.0100 -6220347.9681
## 1000 29148815340.2866 nan 0.0100 3430101.0148
## 1020 28950026020.1081 nan 0.0100 -30776075.2116
## 1040 28743767771.7757 nan 0.0100 -16495863.8055
## 1060 28516496509.7399 nan 0.0100 3067734.2671
## 1080 28339072869.0373 nan 0.0100 1419186.6218
## 1100 28160484048.5507 nan 0.0100 3583977.3073
## 1120 27979569715.0816 nan 0.0100 2764263.0708
## 1140 27804337520.6169 nan 0.0100 -5346601.8625
## 1160 27644304929.1545 nan 0.0100 -19181743.6533
## 1180 27460683810.2252 nan 0.0100 -3541318.0513
## 1200 27246637656.7750 nan 0.0100 -10777284.3756
## 1220 27084150731.3158 nan 0.0100 -16142783.9798
## 1240 26890625902.0306 nan 0.0100 -5005959.2889
## 1260 26741662936.0258 nan 0.0100 -3393197.1944
## 1280 26594083281.5489 nan 0.0100 -4070737.8673
## 1300 26438647204.3882 nan 0.0100 -30595420.9977
## 1320 26310983985.0401 nan 0.0100 -14815962.9693
## 1340 26153728835.6785 nan 0.0100 -7892630.1673
## 1360 26015255163.5740 nan 0.0100 1946066.2500
## 1380 25873350252.2631 nan 0.0100 599858.5930
## 1400 25723761097.5656 nan 0.0100 -8477232.2870
## 1420 25573345750.3698 nan 0.0100 7323224.6060
## 1440 25419109459.0475 nan 0.0100 1872452.7225
## 1460 25294116471.6926 nan 0.0100 -8727549.2629
## 1480 25155142434.1191 nan 0.0100 -6813897.5657
## 1500 25026330776.8522 nan 0.0100 -7057769.0944
## 1520 24904487955.8593 nan 0.0100 1657756.0344
## 1540 24779319501.8078 nan 0.0100 -31042906.3877
## 1560 24656085525.0681 nan 0.0100 -13806914.5807
## 1580 24538010778.7954 nan 0.0100 -20780995.9257
## 1600 24413614454.1068 nan 0.0100 -6800687.2390
## 1620 24294173184.5484 nan 0.0100 -8576877.8429
## 1640 24177149860.4789 nan 0.0100 -2664520.9357
## 1660 24060354685.4128 nan 0.0100 -13387522.2113
## 1680 23929185775.3283 nan 0.0100 -6881971.9186
## 1700 23812502010.7719 nan 0.0100 -11528545.7859
## 1720 23690163151.5696 nan 0.0100 -1819194.7595
## 1740 23570508523.3131 nan 0.0100 -18016285.7005
## 1760 23473342865.4360 nan 0.0100 -2896293.2901
## 1780 23379317390.9495 nan 0.0100 -4620199.8083
## 1800 23274327115.2064 nan 0.0100 -7066730.9867
## 1820 23159949303.7751 nan 0.0100 -15576074.0956
## 1840 23058583022.4284 nan 0.0100 -9271250.6292
## 1860 22949275504.1880 nan 0.0100 -4774838.9183
## 1880 22855066401.0762 nan 0.0100 -6939800.6518
## 1900 22754110008.1518 nan 0.0100 -4160435.8701
## 1920 22649244942.5578 nan 0.0100 -8845741.0703
## 1940 22542343214.0727 nan 0.0100 -11711040.7311
## 1960 22444655022.1223 nan 0.0100 -7944023.2827
## 1980 22353491035.7835 nan 0.0100 -10795023.7106
## 2000 22259290417.8844 nan 0.0100 -5209699.9538
## 2020 22141952628.0987 nan 0.0100 -13521972.0586
## 2040 22034130265.0569 nan 0.0100 -3092954.2486
## 2060 21952691377.4315 nan 0.0100 -2753526.6507
## 2080 21877845868.3138 nan 0.0100 -3421198.6290
## 2100 21772928977.8791 nan 0.0100 -9351582.3647
## 2120 21690777844.7142 nan 0.0100 2078784.3721
## 2140 21605559305.4806 nan 0.0100 -13597035.1803
## 2160 21520117119.9097 nan 0.0100 1404802.0706
## 2180 21414758133.3418 nan 0.0100 -7456876.7714
## 2200 21313891144.3878 nan 0.0100 3398939.4174
## 2220 21234632624.7114 nan 0.0100 870905.1201
## 2240 21140434883.7338 nan 0.0100 -3602594.7224
## 2260 21034409881.5489 nan 0.0100 -6028123.8456
## 2280 20949113392.0066 nan 0.0100 -11600340.0654
## 2300 20865090731.7584 nan 0.0100 757945.6060
## 2320 20781177800.2714 nan 0.0100 1274469.3764
## 2340 20705732073.6495 nan 0.0100 -9168758.9785
## 2360 20637102640.4566 nan 0.0100 -3020582.3917
## 2380 20558396195.5287 nan 0.0100 -7200508.4097
## 2400 20474119666.5391 nan 0.0100 -4710174.0920
## 2420 20396101253.9940 nan 0.0100 -4845690.3008
## 2440 20325592182.0668 nan 0.0100 -458028.3276
## 2460 20251107679.0697 nan 0.0100 463420.4108
## 2480 20177535601.0423 nan 0.0100 -6143975.8797
## 2500 20099939135.3065 nan 0.0100 -7496461.6163
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 259434594785.4381 nan 0.0100 3000179731.9940
## 2 256463976279.4037 nan 0.0100 3278259634.7348
## 3 253476555740.7105 nan 0.0100 3370503804.5416
## 4 250575697362.3763 nan 0.0100 2975802369.9356
## 5 247687650396.6333 nan 0.0100 2952539933.0140
## 6 244828436039.1803 nan 0.0100 2569517241.7767
## 7 242017432545.2323 nan 0.0100 2381467421.7829
## 8 239369981427.6997 nan 0.0100 2096227301.2889
## 9 236626222398.6537 nan 0.0100 2554226086.7010
## 10 233890628962.8315 nan 0.0100 2758963432.7829
## 20 209851013382.0952 nan 0.0100 1884240888.7849
## 40 172323016616.5103 nan 0.0100 1485425288.1693
## 60 144569903729.4003 nan 0.0100 1052324308.3564
## 80 123950851813.4623 nan 0.0100 760094644.6244
## 100 108323965010.0242 nan 0.0100 440156967.3826
## 120 95953755025.1469 nan 0.0100 360837570.0205
## 140 85981846929.2349 nan 0.0100 302997986.7363
## 160 77885181084.1898 nan 0.0100 335244073.9328
## 180 71461742694.9997 nan 0.0100 288258203.2503
## 200 66107898500.6362 nan 0.0100 202295208.9710
## 220 61755059642.2564 nan 0.0100 194770502.4534
## 240 57979323027.9925 nan 0.0100 142584825.1674
## 260 54778444333.7160 nan 0.0100 112138911.0320
## 280 52099233438.2025 nan 0.0100 80741632.5643
## 300 49880026371.5010 nan 0.0100 29475011.3218
## 320 47957370210.0275 nan 0.0100 27336905.7207
## 340 46351888631.7414 nan 0.0100 19680707.2562
## 360 44937533578.0538 nan 0.0100 43283920.8409
## 380 43703701767.2833 nan 0.0100 22864947.8885
## 400 42648907990.8857 nan 0.0100 37148261.6513
## 420 41707224242.4075 nan 0.0100 33937731.6017
## 440 40790356442.2230 nan 0.0100 -3930920.1145
## 460 40022938850.5048 nan 0.0100 -32955706.3094
## 480 39286706551.3328 nan 0.0100 16397840.1666
## 500 38677323192.2939 nan 0.0100 -13659870.2821
## 520 38129514293.4732 nan 0.0100 14584965.6168
## 540 37607235017.4765 nan 0.0100 12032496.9604
## 560 37138657699.4476 nan 0.0100 5894412.3259
## 580 36675246007.2905 nan 0.0100 14389253.1427
## 600 36260469280.6708 nan 0.0100 -34273264.4044
## 620 35910362784.0412 nan 0.0100 -2979881.3596
## 640 35546124585.4122 nan 0.0100 -8906145.4817
## 660 35221329879.0258 nan 0.0100 4361765.3333
## 680 34890687249.6716 nan 0.0100 -38767547.0555
## 700 34564666331.3112 nan 0.0100 -4502960.3549
## 720 34264814722.8316 nan 0.0100 1056204.4653
## 740 33977474041.9635 nan 0.0100 -6458214.0309
## 760 33660311971.9521 nan 0.0100 -7422968.2291
## 780 33366764872.3233 nan 0.0100 -27018167.9976
## 800 33078520268.7733 nan 0.0100 -16918506.1748
## 820 32797019854.3340 nan 0.0100 3717075.2293
## 840 32566808806.7266 nan 0.0100 4320209.1422
## 860 32297969681.0555 nan 0.0100 -14168064.3566
## 880 32046223854.3197 nan 0.0100 -10888893.6125
## 900 31807310457.0741 nan 0.0100 -16780894.2782
## 920 31588547380.9644 nan 0.0100 6253532.0397
## 940 31336868076.7598 nan 0.0100 -20305589.5378
## 960 31121334204.8675 nan 0.0100 -19685999.3100
## 980 30918522696.5303 nan 0.0100 -16677839.2601
## 1000 30707236639.7068 nan 0.0100 -9698276.3119
## 1020 30474969465.2048 nan 0.0100 2298272.2996
## 1040 30288200677.5651 nan 0.0100 1753384.2990
## 1060 30129932321.5479 nan 0.0100 -6653691.8866
## 1080 29969089203.2896 nan 0.0100 2281172.7513
## 1100 29797429159.5853 nan 0.0100 -6944554.3893
## 1120 29617414003.3045 nan 0.0100 -7127151.8888
## 1140 29432008278.2955 nan 0.0100 -4386188.3483
## 1160 29247383273.0723 nan 0.0100 -18493951.1166
## 1180 29074878368.3766 nan 0.0100 -13734282.2479
## 1200 28896366419.0964 nan 0.0100 -10570383.4664
## 1220 28720083694.0854 nan 0.0100 -15353915.4530
## 1240 28585973261.2255 nan 0.0100 37228.4145
## 1260 28420641137.8735 nan 0.0100 -10365192.3520
## 1280 28245675214.8177 nan 0.0100 -11469577.2432
## 1300 28102756376.1078 nan 0.0100 -15492316.7334
## 1320 27937926778.4869 nan 0.0100 738758.5871
## 1340 27773913954.3401 nan 0.0100 3527412.9819
## 1360 27616075324.9328 nan 0.0100 9852770.0930
## 1380 27470779357.9226 nan 0.0100 -2042552.3081
## 1400 27320337867.2526 nan 0.0100 -21507341.3563
## 1420 27172042731.0470 nan 0.0100 -8092031.8088
## 1440 27027693100.1674 nan 0.0100 -9887602.6570
## 1460 26905591648.8789 nan 0.0100 -8854326.7519
## 1480 26793050404.6108 nan 0.0100 -3806365.0995
## 1500 26646813312.5302 nan 0.0100 1073496.6187
## 1520 26541570655.9676 nan 0.0100 3493645.2361
## 1540 26428031907.1998 nan 0.0100 -353660.6458
## 1560 26294762518.7099 nan 0.0100 -16750682.9760
## 1580 26186749932.3592 nan 0.0100 -150819.0113
## 1600 26030794986.9553 nan 0.0100 -922483.8734
## 1620 25909537059.2822 nan 0.0100 -7278358.8658
## 1640 25756921163.4955 nan 0.0100 -3284632.4637
## 1660 25638096990.0360 nan 0.0100 41450.5283
## 1680 25517756566.0733 nan 0.0100 -1438315.0381
## 1700 25398932161.7982 nan 0.0100 -3245114.3141
## 1720 25281407371.7977 nan 0.0100 1104731.8998
## 1740 25151213821.5205 nan 0.0100 -6132175.0861
## 1760 25031344148.7776 nan 0.0100 6536758.3549
## 1780 24922904429.0165 nan 0.0100 2365399.5659
## 1800 24817206267.0234 nan 0.0100 -6268004.8921
## 1820 24720140670.5664 nan 0.0100 -6688455.7173
## 1840 24604277981.9476 nan 0.0100 -3683702.7416
## 1860 24499352711.3962 nan 0.0100 -3458941.0939
## 1880 24400706770.2407 nan 0.0100 -2879606.5505
## 1900 24293792426.7744 nan 0.0100 -2283917.7586
## 1920 24185760773.6124 nan 0.0100 -15091471.8569
## 1940 24106483702.6184 nan 0.0100 603311.3162
## 1960 24008210104.0602 nan 0.0100 -6990231.9191
## 1980 23906212449.5826 nan 0.0100 -6284092.5098
## 2000 23814658714.0074 nan 0.0100 -6709475.9437
## 2020 23714846173.5115 nan 0.0100 -3556897.7758
## 2040 23615379512.4933 nan 0.0100 1446242.6220
## 2060 23529318098.7808 nan 0.0100 -4977466.3901
## 2080 23421529555.2135 nan 0.0100 -5426004.0823
## 2100 23319877640.1320 nan 0.0100 -4354503.5162
## 2120 23236220283.0248 nan 0.0100 1668159.6232
## 2140 23157736219.2829 nan 0.0100 -6048154.0176
## 2160 23065150366.0072 nan 0.0100 -9763463.4365
## 2180 22971481511.9230 nan 0.0100 -2049138.4166
## 2200 22892954010.9773 nan 0.0100 -5089642.5194
## 2220 22809199885.9797 nan 0.0100 -4348696.5804
## 2240 22698111201.7724 nan 0.0100 -4056074.7604
## 2260 22630428762.6528 nan 0.0100 -10702390.8926
## 2280 22550807639.0517 nan 0.0100 -1820461.3899
## 2300 22464149660.9779 nan 0.0100 -7297008.7033
## 2320 22390860951.0828 nan 0.0100 -98064.0776
## 2340 22298471106.4470 nan 0.0100 -7649536.1023
## 2360 22233229719.1097 nan 0.0100 -9555605.7224
## 2380 22155065706.9245 nan 0.0100 -7173537.3079
## 2400 22082545907.3723 nan 0.0100 -3805573.3698
## 2420 22012138272.3429 nan 0.0100 1736046.2244
## 2440 21932999639.1242 nan 0.0100 -12873391.7682
## 2460 21864734966.5210 nan 0.0100 -2970102.6639
## 2480 21772502355.1465 nan 0.0100 1098741.3925
## 2500 21700668977.5444 nan 0.0100 -5087262.0256#out of sample testing of gbm
gbmPredictions <- predict(model5_gbm,test_data)
gbm_results<-data.frame( RMSE = RMSE(gbmPredictions, test_data$price),
Rsquare = R2(gbmPredictions, test_data$price))
gbm_results## RMSE Rsquare
## 1 189858.3 0.8782757models <- c("Linear Regression", "Regression Trees", "Support Vector Machines", "Random Forests", "Gradient Boosting Methods")
resultSummary = cbind(models, rbind(lr_results, tree_results, svm_results, rf_results, gbm_results))
resultSummary## models RMSE Rsquare
## 1 Linear Regression 204467.4 0.8570818
## 2 Regression Trees 257971.1 0.7706503
## 3 Support Vector Machines 179665.0 0.8936471
## 4 Random Forests 197243.4 0.8713550
## 5 Gradient Boosting Methods 189858.3 0.8782757Our constructed Support Vector Machines seem to be most accurate in out of sample testing. We will focus on the last three models for ensembling.
7 Stacking
stackingControl <- trainControl(method="cv", number=5, verboseIter = FALSE)
#first, lets look at the best tunes from each of the single underlying models such that we can take the chosen parameters for stacking
model3_svm$bestTune## sigma C
## 8 0.01226624 32model4_randomForests$bestTune## mtry splitrule min.node.size
## 6 47 extratrees 5model5_gbm$bestTune## n.trees interaction.depth shrinkage n.minobsinnode
## 306 2500 5 0.01 10modelList <- caretList(
price ~ total_floor_area + district + london_zone + number_habitable_rooms + co2_emissions_potential + distance_to_station +water_company+property_type+latitude+ longitude + average_income + property_type,
train_data,
trControl = stackingControl,
tuneList = list(
#we create a model list with the best tunes of each model
svm = caretModelSpec(method = "svmRadial", tuneGrid = data.frame(sigma = 0.01226624 , C = 32)),
ranger = caretModelSpec(method = "ranger", tuneGrid = data.frame(mtry=47,splitrule="extratrees",min.node.size=5)),
gbm = caretModelSpec(method = "gbm", tuneGrid = data.frame(n.trees = 2500, interaction.depth = 5, shrinkage = 0.01, n.minobsinnode = 10))
)
)## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 239364856226.2546 nan 0.0100 2947016420.6332
## 2 236541801155.6250 nan 0.0100 2611181255.5517
## 3 233693301501.8241 nan 0.0100 2844361247.1681
## 4 230898101892.4684 nan 0.0100 2748350777.7489
## 5 228309845426.2291 nan 0.0100 2414733862.4764
## 6 225830072948.1818 nan 0.0100 2379867461.4105
## 7 223276863935.5284 nan 0.0100 2225612484.2260
## 8 220683976567.0053 nan 0.0100 2256415497.3098
## 9 218114230888.3553 nan 0.0100 2269522191.1517
## 10 215659107802.4717 nan 0.0100 2354433155.0562
## 20 193675456181.8150 nan 0.0100 1866654813.3427
## 40 159207165330.2831 nan 0.0100 1484001941.2202
## 60 133832661014.6379 nan 0.0100 926280072.7556
## 80 114655441005.0339 nan 0.0100 721543631.0325
## 100 100127204314.3730 nan 0.0100 491759409.9359
## 120 89059428294.6894 nan 0.0100 342516342.9585
## 140 80141100524.4390 nan 0.0100 399861549.6197
## 160 72886342239.1079 nan 0.0100 329843348.3780
## 180 66961297385.4074 nan 0.0100 180445801.2634
## 200 62048656146.1825 nan 0.0100 189633613.4797
## 220 58038969789.0708 nan 0.0100 207658541.5785
## 240 54710857630.3870 nan 0.0100 130327377.1504
## 260 51876970150.5845 nan 0.0100 90761874.6318
## 280 49501695666.4617 nan 0.0100 67470457.4855
## 300 47421274782.4806 nan 0.0100 80916030.3217
## 320 45726612253.1586 nan 0.0100 27751982.4932
## 340 44278617376.7239 nan 0.0100 29722610.0269
## 360 43015653104.4384 nan 0.0100 55628516.8622
## 380 41943723555.8523 nan 0.0100 11152394.1245
## 400 41032548886.7762 nan 0.0100 19713208.8926
## 420 40212530427.0153 nan 0.0100 25858470.6723
## 440 39459540442.8951 nan 0.0100 22456902.1319
## 460 38790353519.5998 nan 0.0100 -6028682.3721
## 480 38260575690.1908 nan 0.0100 26858957.7537
## 500 37768773570.3088 nan 0.0100 -8773102.8722
## 520 37296508275.4617 nan 0.0100 -2770706.8564
## 540 36862246513.0122 nan 0.0100 -22511269.1517
## 560 36474172231.3778 nan 0.0100 8322865.7533
## 580 36068560232.7834 nan 0.0100 -5773607.3197
## 600 35652112380.5688 nan 0.0100 -8688597.7129
## 620 35299221747.4725 nan 0.0100 3774325.4687
## 640 34931239368.2139 nan 0.0100 3993089.8011
## 660 34596985446.5466 nan 0.0100 -21848784.3838
## 680 34282823369.8271 nan 0.0100 -1827905.9012
## 700 34015038262.1070 nan 0.0100 -7460067.3536
## 720 33750326243.0152 nan 0.0100 -11970557.7319
## 740 33429745190.5926 nan 0.0100 -10273045.3754
## 760 33100507854.2345 nan 0.0100 -157943.3401
## 780 32846327069.9204 nan 0.0100 -8718941.6000
## 800 32582236570.9375 nan 0.0100 -2229639.4546
## 820 32313272494.8475 nan 0.0100 -7399557.5585
## 840 32114853329.6390 nan 0.0100 -20131313.2593
## 860 31874338100.4010 nan 0.0100 -12058410.6601
## 880 31657675254.7444 nan 0.0100 -10207511.2092
## 900 31433048592.2919 nan 0.0100 -7853169.6933
## 920 31192366651.6854 nan 0.0100 -17684108.7569
## 940 30993129217.7645 nan 0.0100 -18640341.2022
## 960 30754919896.8320 nan 0.0100 -13915934.6370
## 980 30578436190.5561 nan 0.0100 1616665.4108
## 1000 30381262625.4259 nan 0.0100 -12887474.3024
## 1020 30201767333.6628 nan 0.0100 -1690255.3137
## 1040 30012874529.5883 nan 0.0100 -14897741.5285
## 1060 29866706030.7615 nan 0.0100 -2297141.9883
## 1080 29696156825.2094 nan 0.0100 -2118396.8528
## 1100 29533684177.7668 nan 0.0100 -14734462.7195
## 1120 29401170267.4421 nan 0.0100 -15329600.5365
## 1140 29186625520.6995 nan 0.0100 -18895605.7022
## 1160 28988622492.0837 nan 0.0100 -14759084.9520
## 1180 28833761610.5348 nan 0.0100 -5290151.8835
## 1200 28652228641.5923 nan 0.0100 -23288249.9817
## 1220 28480330264.6791 nan 0.0100 -4161460.8235
## 1240 28313835137.2139 nan 0.0100 -7962749.3115
## 1260 28173008498.2269 nan 0.0100 -7652343.0312
## 1280 28040169653.0185 nan 0.0100 -10168036.5027
## 1300 27918625328.1095 nan 0.0100 -12685369.8859
## 1320 27760251961.4076 nan 0.0100 -7424543.1669
## 1340 27623121211.3733 nan 0.0100 -9000978.8789
## 1360 27502354299.7207 nan 0.0100 -4508289.9482
## 1380 27375555618.9606 nan 0.0100 -15731320.9197
## 1400 27252762895.1705 nan 0.0100 -8797912.6042
## 1420 27119142132.2909 nan 0.0100 -12752717.6941
## 1440 26992268205.0603 nan 0.0100 -5603821.9232
## 1460 26881170926.1609 nan 0.0100 -4585744.8785
## 1480 26787135873.2878 nan 0.0100 -14774578.3803
## 1500 26628529988.8799 nan 0.0100 -2330255.6347
## 1520 26500328887.6556 nan 0.0100 -14803406.5604
## 1540 26393811853.1298 nan 0.0100 -6151010.4420
## 1560 26279631671.7517 nan 0.0100 -4876670.5660
## 1580 26171474405.4685 nan 0.0100 -18958495.0964
## 1600 26060854310.8089 nan 0.0100 -10997491.8135
## 1620 25931303687.7113 nan 0.0100 -474015.1667
## 1640 25824754887.2443 nan 0.0100 -4501939.7403
## 1660 25698348850.6802 nan 0.0100 -14842302.4020
## 1680 25565274935.7309 nan 0.0100 -9397024.5513
## 1700 25455562145.3709 nan 0.0100 -10350918.2209
## 1720 25346631111.1763 nan 0.0100 -6471483.0812
## 1740 25236351255.8882 nan 0.0100 -26011595.3618
## 1760 25132077419.4184 nan 0.0100 -679237.7816
## 1780 25044747534.4941 nan 0.0100 -7191359.3913
## 1800 24948313964.0451 nan 0.0100 -10834627.7678
## 1820 24858552955.6383 nan 0.0100 849253.6291
## 1840 24750645809.2963 nan 0.0100 -7921612.3413
## 1860 24677586624.4155 nan 0.0100 -4447452.5694
## 1880 24594951525.7966 nan 0.0100 -14585134.1808
## 1900 24509824717.6218 nan 0.0100 -5474314.8116
## 1920 24418205362.4425 nan 0.0100 -16471054.6272
## 1940 24324324529.4349 nan 0.0100 -11060691.1492
## 1960 24216492985.7183 nan 0.0100 -11672422.0811
## 1980 24118143175.6420 nan 0.0100 -8627554.6456
## 2000 24014665279.6585 nan 0.0100 -16351294.6142
## 2020 23905641975.0352 nan 0.0100 1466185.2197
## 2040 23805831860.4711 nan 0.0100 -7434345.1335
## 2060 23699398690.5938 nan 0.0100 -3310193.8644
## 2080 23602732751.6072 nan 0.0100 -9727355.8439
## 2100 23526340976.0845 nan 0.0100 -9058744.9404
## 2120 23429515116.8203 nan 0.0100 -1716560.6859
## 2140 23344044943.8963 nan 0.0100 -15505942.4409
## 2160 23246445538.5329 nan 0.0100 -16025458.7480
## 2180 23160807206.9759 nan 0.0100 -5125533.7123
## 2200 23077802582.0380 nan 0.0100 -9794910.2508
## 2220 22993885095.3278 nan 0.0100 -7469167.5491
## 2240 22907099042.8152 nan 0.0100 -4030648.7446
## 2260 22827837035.2101 nan 0.0100 -6981550.2178
## 2280 22741425425.0105 nan 0.0100 -10156908.1467
## 2300 22665421427.4754 nan 0.0100 -14922991.4679
## 2320 22578556495.0706 nan 0.0100 -6803427.8360
## 2340 22500928585.5548 nan 0.0100 2119955.6699
## 2360 22431539234.9627 nan 0.0100 -11961222.2085
## 2380 22339299697.2348 nan 0.0100 -3523253.6267
## 2400 22250824134.4213 nan 0.0100 -13110464.5894
## 2420 22183718054.8335 nan 0.0100 -3589325.3453
## 2440 22120065004.2212 nan 0.0100 -15501716.8057
## 2460 22052983963.7299 nan 0.0100 -6475033.1615
## 2480 21978003126.1033 nan 0.0100 -2368433.7359
## 2500 21912946351.5861 nan 0.0100 -6067635.0663
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 269602285735.2189 nan 0.0100 3048969427.0397
## 2 266377279630.7963 nan 0.0100 3131868364.5243
## 3 263166517180.3232 nan 0.0100 3180291962.6885
## 4 260242958819.6727 nan 0.0100 2975322759.2413
## 5 257132542474.1814 nan 0.0100 3374306995.0960
## 6 254052548896.2721 nan 0.0100 3128506186.7908
## 7 251153848614.5147 nan 0.0100 2926271315.7043
## 8 248238804948.0113 nan 0.0100 3163672527.2259
## 9 245365051327.2104 nan 0.0100 2737705096.5217
## 10 242392906120.1180 nan 0.0100 3070889590.5498
## 20 217014916140.4726 nan 0.0100 2215393672.7390
## 40 176928958976.7605 nan 0.0100 1558992933.8308
## 60 148040505903.2070 nan 0.0100 1148370366.1651
## 80 126363662371.9322 nan 0.0100 825484450.7120
## 100 109996275273.6150 nan 0.0100 579360275.3074
## 120 96996895081.1478 nan 0.0100 409051242.7546
## 140 86785487251.7152 nan 0.0100 359149985.8217
## 160 78875341122.0777 nan 0.0100 289987883.0162
## 180 72258881617.2722 nan 0.0100 247724125.7715
## 200 66713183679.9314 nan 0.0100 268097148.4828
## 220 62312035734.6366 nan 0.0100 180340082.0000
## 240 58456959779.1468 nan 0.0100 168966993.7161
## 260 55242307799.1134 nan 0.0100 61794583.4446
## 280 52761250715.9892 nan 0.0100 84710932.8697
## 300 50606286762.8867 nan 0.0100 67155978.1087
## 320 48844069554.9927 nan 0.0100 60569376.3428
## 340 47325019699.6337 nan 0.0100 55606113.3883
## 360 45988059143.8199 nan 0.0100 27509400.1950
## 380 44905156532.3840 nan 0.0100 22726873.6552
## 400 43883132378.7923 nan 0.0100 5821793.2269
## 420 42950123621.5358 nan 0.0100 4169851.2786
## 440 42195082882.0539 nan 0.0100 -13993572.0999
## 460 41546123677.8023 nan 0.0100 18022775.1599
## 480 40917063262.2998 nan 0.0100 -23261926.4616
## 500 40323331231.2100 nan 0.0100 -2134337.2173
## 520 39819623341.7679 nan 0.0100 -20498074.9489
## 540 39323315682.1763 nan 0.0100 -8475011.5124
## 560 38843231296.1382 nan 0.0100 10461553.4106
## 580 38416665158.8907 nan 0.0100 8501550.3130
## 600 37938316715.3932 nan 0.0100 -3836398.2670
## 620 37521170395.5105 nan 0.0100 -6011079.0530
## 640 37155598864.7724 nan 0.0100 -10336869.3941
## 660 36818443013.3724 nan 0.0100 -22493442.4680
## 680 36493404792.6134 nan 0.0100 -12691000.4000
## 700 36208149715.6930 nan 0.0100 -18692554.3533
## 720 35877216214.4882 nan 0.0100 -13982878.4388
## 740 35550575483.5049 nan 0.0100 -19176645.1229
## 760 35241495815.0455 nan 0.0100 -19319171.6026
## 780 34931461138.6739 nan 0.0100 -25721857.7716
## 800 34613438062.9461 nan 0.0100 -12535535.0016
## 820 34373512793.1868 nan 0.0100 -27433016.1549
## 840 34146563447.3469 nan 0.0100 -22343836.2441
## 860 33875626825.7980 nan 0.0100 7886411.5139
## 880 33648447532.5227 nan 0.0100 -10425254.3460
## 900 33387361261.5199 nan 0.0100 -5101149.0427
## 920 33149021466.1066 nan 0.0100 -9805236.9617
## 940 32929771111.2467 nan 0.0100 -17789108.5269
## 960 32677954205.2113 nan 0.0100 -2415888.4157
## 980 32451927284.6358 nan 0.0100 11787609.8544
## 1000 32227197036.2736 nan 0.0100 -1356144.5770
## 1020 31990232875.5995 nan 0.0100 -34094025.9965
## 1040 31766049479.4904 nan 0.0100 -3302779.9079
## 1060 31539932782.7239 nan 0.0100 -17694954.5831
## 1080 31325857293.4039 nan 0.0100 799982.8422
## 1100 31129054763.4346 nan 0.0100 -14164473.1909
## 1120 30919452517.3517 nan 0.0100 -13767403.8809
## 1140 30698732905.6853 nan 0.0100 809966.0689
## 1160 30513435972.8159 nan 0.0100 -16365717.1420
## 1180 30287758711.3441 nan 0.0100 -5745435.0369
## 1200 30089538947.0334 nan 0.0100 -259905.0708
## 1220 29896565975.9876 nan 0.0100 -17047584.2045
## 1240 29675958604.5729 nan 0.0100 -14513793.4901
## 1260 29460309450.4921 nan 0.0100 -20658908.8369
## 1280 29314395141.5957 nan 0.0100 -12254808.4827
## 1300 29152849639.3940 nan 0.0100 -5519312.3618
## 1320 28983213933.0585 nan 0.0100 -2439489.9579
## 1340 28790628169.5928 nan 0.0100 -1531378.8954
## 1360 28588511078.4377 nan 0.0100 -11928043.7360
## 1380 28421182578.9835 nan 0.0100 -8326512.1750
## 1400 28225418061.7351 nan 0.0100 -16381050.2415
## 1420 28063695613.9771 nan 0.0100 -9677342.4764
## 1440 27936426510.0252 nan 0.0100 -13364297.8496
## 1460 27786799124.9895 nan 0.0100 1794661.2473
## 1480 27636011420.3979 nan 0.0100 -8828768.7471
## 1500 27492376573.4536 nan 0.0100 -19187666.5429
## 1520 27343729405.9474 nan 0.0100 -36503809.0741
## 1540 27210078257.2163 nan 0.0100 -11503792.9454
## 1560 27083740343.8028 nan 0.0100 -15564393.9146
## 1580 26964722072.8165 nan 0.0100 -6932450.2865
## 1600 26839744760.2360 nan 0.0100 -12813908.4808
## 1620 26729526208.1132 nan 0.0100 -16423068.9165
## 1640 26574373318.5860 nan 0.0100 -15079932.3790
## 1660 26444500541.7734 nan 0.0100 -9784533.8614
## 1680 26326888403.6237 nan 0.0100 -16066818.1625
## 1700 26192044164.3621 nan 0.0100 -12673550.4111
## 1720 26055857859.1758 nan 0.0100 -12307594.3077
## 1740 25915852496.1768 nan 0.0100 -146908.2741
## 1760 25802182127.9267 nan 0.0100 -11734383.3990
## 1780 25692462300.8570 nan 0.0100 -21343321.5102
## 1800 25585001046.3625 nan 0.0100 -10492122.9757
## 1820 25492648709.9246 nan 0.0100 -24947788.2124
## 1840 25390294602.3646 nan 0.0100 -15470232.6707
## 1860 25281809036.5094 nan 0.0100 -15595283.5930
## 1880 25189321218.7811 nan 0.0100 -6575211.0255
## 1900 25090607275.2481 nan 0.0100 -17555054.1324
## 1920 24979179438.2588 nan 0.0100 -7592916.6100
## 1940 24871000433.7186 nan 0.0100 -8384400.7985
## 1960 24761624485.5747 nan 0.0100 -10870090.4581
## 1980 24638122999.4501 nan 0.0100 -6745582.9260
## 2000 24533307178.8799 nan 0.0100 -11818045.3587
## 2020 24418432808.8751 nan 0.0100 -6810494.7063
## 2040 24320720411.2499 nan 0.0100 -20193961.7276
## 2060 24214043357.7873 nan 0.0100 -25697128.3712
## 2080 24120464281.6622 nan 0.0100 -17276164.1208
## 2100 24016158242.5432 nan 0.0100 -4946577.2772
## 2120 23900934435.0410 nan 0.0100 -18490046.3196
## 2140 23814935886.9511 nan 0.0100 -4682577.1630
## 2160 23743515647.7893 nan 0.0100 -4780896.8993
## 2180 23619355302.0807 nan 0.0100 -859327.9484
## 2200 23531362967.1086 nan 0.0100 -770427.1541
## 2220 23430054842.2791 nan 0.0100 -6566305.8874
## 2240 23345171234.0129 nan 0.0100 -10383124.5703
## 2260 23264965473.8560 nan 0.0100 -7428689.9671
## 2280 23182248725.9448 nan 0.0100 -7225741.0770
## 2300 23075909443.6945 nan 0.0100 -15102868.6651
## 2320 22971542685.4690 nan 0.0100 -7387379.3336
## 2340 22873199904.0868 nan 0.0100 -2594166.4887
## 2360 22768652444.0798 nan 0.0100 -14669260.6875
## 2380 22682021050.0567 nan 0.0100 -5017887.1921
## 2400 22597072267.9765 nan 0.0100 -7376558.0737
## 2420 22501330086.4055 nan 0.0100 -9318268.7504
## 2440 22415406795.1001 nan 0.0100 -4665448.2733
## 2460 22325829909.0769 nan 0.0100 -4869883.0551
## 2480 22240582949.2583 nan 0.0100 -6974430.6752
## 2500 22155931775.9843 nan 0.0100 -3408941.5045
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 265586943664.6453 nan 0.0100 3536872206.0447
## 2 262384735816.6255 nan 0.0100 3160235152.6700
## 3 258989724686.4830 nan 0.0100 3069694935.9760
## 4 255977086651.1089 nan 0.0100 2817995758.6110
## 5 253046421022.8529 nan 0.0100 2979045048.5800
## 6 250083739904.5429 nan 0.0100 3094600960.1282
## 7 247274459349.0473 nan 0.0100 2808480618.8074
## 8 244242003770.3038 nan 0.0100 2990324683.4639
## 9 241308863934.3782 nan 0.0100 2640099992.9036
## 10 238598251012.1779 nan 0.0100 2515886536.0445
## 20 213599229606.1421 nan 0.0100 2184741540.0642
## 40 174190799041.2134 nan 0.0100 1447617301.4300
## 60 144947844367.8721 nan 0.0100 1271244880.4653
## 80 123727892629.2391 nan 0.0100 862859379.8476
## 100 107518352365.4610 nan 0.0100 647624927.5508
## 120 94600742001.5875 nan 0.0100 542172106.1462
## 140 84429408817.5833 nan 0.0100 395283999.6573
## 160 76500899121.9086 nan 0.0100 347364921.5259
## 180 69931320622.4307 nan 0.0100 203323361.4138
## 200 64540898211.4604 nan 0.0100 204860396.7936
## 220 60191931411.9031 nan 0.0100 154454453.6990
## 240 56512988274.7992 nan 0.0100 101343952.5285
## 260 53429223556.9477 nan 0.0100 110044584.4656
## 280 50881614837.1971 nan 0.0100 71573695.7759
## 300 48735630077.3596 nan 0.0100 100038360.1876
## 320 47057948303.1209 nan 0.0100 63342387.4806
## 340 45492704098.8349 nan 0.0100 32117842.4732
## 360 44184690062.1480 nan 0.0100 20230825.5021
## 380 43101867330.4835 nan 0.0100 22692893.1873
## 400 42170803545.1764 nan 0.0100 5363748.8729
## 420 41273987789.2980 nan 0.0100 629648.7782
## 440 40469452477.4853 nan 0.0100 14074633.2261
## 460 39790095128.0713 nan 0.0100 -1081277.7584
## 480 39130964371.6074 nan 0.0100 16426967.0101
## 500 38590180098.6765 nan 0.0100 16497116.6893
## 520 38077157873.9502 nan 0.0100 15655479.8669
## 540 37616190087.8235 nan 0.0100 9833901.4255
## 560 37119150270.4938 nan 0.0100 -9188270.6614
## 580 36693042067.9986 nan 0.0100 7016091.3377
## 600 36312883982.9611 nan 0.0100 -2493102.9580
## 620 35918524568.3934 nan 0.0100 8482963.2862
## 640 35525263349.9665 nan 0.0100 -4769552.6324
## 660 35183732583.1655 nan 0.0100 4725528.2089
## 680 34859844280.4265 nan 0.0100 4489886.1633
## 700 34532118796.0597 nan 0.0100 -16746493.0846
## 720 34219837045.5565 nan 0.0100 -9612125.3255
## 740 33878692020.6514 nan 0.0100 -8050281.5959
## 760 33600207914.7040 nan 0.0100 -4146654.5135
## 780 33337099046.9629 nan 0.0100 -4453476.3232
## 800 33108344464.8463 nan 0.0100 -5493043.6628
## 820 32849194374.7800 nan 0.0100 -12851770.3314
## 840 32615566128.0625 nan 0.0100 -5299234.2627
## 860 32344140725.5619 nan 0.0100 -27011406.2969
## 880 32113163274.9849 nan 0.0100 -5033001.8718
## 900 31899739461.1785 nan 0.0100 -14249204.1947
## 920 31664494839.3802 nan 0.0100 708509.8222
## 940 31451671723.2440 nan 0.0100 -6661955.2286
## 960 31215938213.0656 nan 0.0100 -7837430.5998
## 980 30994240200.7309 nan 0.0100 -5695139.0356
## 1000 30781344178.0786 nan 0.0100 -17294002.8095
## 1020 30575847593.9906 nan 0.0100 -4081306.9988
## 1040 30370318272.2725 nan 0.0100 969746.0500
## 1060 30154807409.1625 nan 0.0100 -8788646.5107
## 1080 29960552880.1505 nan 0.0100 -18813102.7704
## 1100 29770099507.2786 nan 0.0100 -7680240.2354
## 1120 29568092549.6703 nan 0.0100 -17547310.9047
## 1140 29378657163.9971 nan 0.0100 -15688160.1097
## 1160 29183490886.3513 nan 0.0100 -12419437.2698
## 1180 28993451350.6747 nan 0.0100 -5361966.3694
## 1200 28802204219.0647 nan 0.0100 -7161780.7437
## 1220 28638982395.9808 nan 0.0100 2347548.5381
## 1240 28490122831.4880 nan 0.0100 2468737.2568
## 1260 28330399894.7232 nan 0.0100 -9870995.9515
## 1280 28182972896.5961 nan 0.0100 -4596731.3002
## 1300 28021770013.1421 nan 0.0100 -20935960.5352
## 1320 27876780641.0526 nan 0.0100 -18132259.3658
## 1340 27739790597.1026 nan 0.0100 -16142261.4277
## 1360 27553585394.7764 nan 0.0100 -12964007.8773
## 1380 27427905123.7624 nan 0.0100 -19324920.5817
## 1400 27279973576.2534 nan 0.0100 -7541620.3148
## 1420 27140921361.8509 nan 0.0100 -10349073.4147
## 1440 27014030867.3647 nan 0.0100 877482.6740
## 1460 26896605370.1815 nan 0.0100 -8255793.2680
## 1480 26752298529.5552 nan 0.0100 589069.0704
## 1500 26613268297.3173 nan 0.0100 -5855570.3881
## 1520 26463233353.5327 nan 0.0100 3371552.7415
## 1540 26342189311.9133 nan 0.0100 -7718295.0572
## 1560 26215195138.5452 nan 0.0100 -2942019.2530
## 1580 26110524052.5396 nan 0.0100 -10207475.3535
## 1600 26003909539.7653 nan 0.0100 -4079952.8446
## 1620 25869793656.0953 nan 0.0100 -7367577.0939
## 1640 25737682847.7478 nan 0.0100 -6861465.4528
## 1660 25625282173.3119 nan 0.0100 -9329813.9561
## 1680 25480611893.7447 nan 0.0100 -1399243.4898
## 1700 25373894764.3512 nan 0.0100 -12574970.7388
## 1720 25271306257.2205 nan 0.0100 -7738285.3426
## 1740 25143557946.8106 nan 0.0100 -1396406.6405
## 1760 25027473237.3673 nan 0.0100 -4696001.7983
## 1780 24892098617.4218 nan 0.0100 -5215237.8466
## 1800 24774877482.4654 nan 0.0100 -15402485.9586
## 1820 24670742104.9592 nan 0.0100 -2531519.8269
## 1840 24535922988.6258 nan 0.0100 -13400632.5626
## 1860 24432694871.0566 nan 0.0100 -8578344.0708
## 1880 24329012978.7759 nan 0.0100 -5942143.6028
## 1900 24208232597.1418 nan 0.0100 784626.7561
## 1920 24102451598.6554 nan 0.0100 -5656118.2082
## 1940 23994344765.2661 nan 0.0100 -866921.6923
## 1960 23908404325.4763 nan 0.0100 -20159164.2190
## 1980 23799667996.0985 nan 0.0100 -6778087.3594
## 2000 23681082912.4357 nan 0.0100 -15446682.5898
## 2020 23579454657.8024 nan 0.0100 -6358246.2637
## 2040 23476906347.1914 nan 0.0100 -1633999.3218
## 2060 23381850463.2723 nan 0.0100 -5145930.1651
## 2080 23272994428.8914 nan 0.0100 -7387559.5634
## 2100 23173184178.4892 nan 0.0100 -8268863.7678
## 2120 23102874770.5649 nan 0.0100 -7059345.7993
## 2140 23011787794.2256 nan 0.0100 -10450661.1179
## 2160 22931448852.8658 nan 0.0100 -14178223.1678
## 2180 22838769825.1473 nan 0.0100 -1401534.9342
## 2200 22735219380.0131 nan 0.0100 -9273236.7609
## 2220 22635009844.4607 nan 0.0100 -8106437.2790
## 2240 22543985698.1738 nan 0.0100 -3748500.8662
## 2260 22463997281.3156 nan 0.0100 -9890262.6113
## 2280 22392433442.0966 nan 0.0100 -4212503.6683
## 2300 22301012371.0420 nan 0.0100 -6413873.6009
## 2320 22219417469.6473 nan 0.0100 -3683574.4026
## 2340 22134538942.0384 nan 0.0100 1360334.6081
## 2360 22038628306.6143 nan 0.0100 -17937397.9302
## 2380 21927336900.9441 nan 0.0100 -7938953.7706
## 2400 21849185897.2702 nan 0.0100 -1701912.3613
## 2420 21760026362.6816 nan 0.0100 -15609661.9279
## 2440 21671146447.9060 nan 0.0100 -6389664.7958
## 2460 21589153980.2770 nan 0.0100 -2305197.5019
## 2480 21512149837.2317 nan 0.0100 -4859509.8116
## 2500 21416204075.8076 nan 0.0100 -6234217.4115
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 256581896039.7480 nan 0.0100 2670530065.5495
## 2 253585039639.1096 nan 0.0100 3010344945.8891
## 3 250829660675.5819 nan 0.0100 2646063805.9862
## 4 247730335384.0731 nan 0.0100 2819920744.7982
## 5 245011371913.3538 nan 0.0100 2580229612.3343
## 6 242317117494.9065 nan 0.0100 2186697030.0647
## 7 239402384958.6161 nan 0.0100 2884968497.7836
## 8 236701630907.4185 nan 0.0100 2371882712.3693
## 9 234027652131.2018 nan 0.0100 2479441805.7697
## 10 231328798071.1668 nan 0.0100 2657766352.0257
## 20 207431672852.8745 nan 0.0100 2119686917.4201
## 40 170433789630.3611 nan 0.0100 1399530978.5854
## 60 143693319119.5778 nan 0.0100 925092940.6010
## 80 122966690888.6102 nan 0.0100 804656397.3332
## 100 107767959520.2660 nan 0.0100 591357601.5336
## 120 95639641148.9012 nan 0.0100 503228768.7437
## 140 86201434472.0988 nan 0.0100 379457863.7950
## 160 78633840274.0392 nan 0.0100 316000681.3995
## 180 72063470409.3842 nan 0.0100 217609901.9806
## 200 66702500441.4845 nan 0.0100 164211236.1690
## 220 62350818233.8390 nan 0.0100 135330208.7422
## 240 58642745561.7303 nan 0.0100 135725111.7084
## 260 55643525658.7847 nan 0.0100 73602469.6558
## 280 53165887070.4443 nan 0.0100 88962857.4998
## 300 51086740008.2888 nan 0.0100 102591239.2115
## 320 49297144976.5051 nan 0.0100 39890584.7237
## 340 47676669037.9017 nan 0.0100 35890880.2201
## 360 46306355128.6141 nan 0.0100 -126437.4422
## 380 45172408368.3795 nan 0.0100 39495654.7747
## 400 44201887200.0234 nan 0.0100 33087823.6894
## 420 43360087410.1276 nan 0.0100 36017800.8789
## 440 42546057237.9439 nan 0.0100 37568044.0772
## 460 41904771446.5102 nan 0.0100 -1595084.8339
## 480 41262316102.4459 nan 0.0100 19379023.7767
## 500 40673947190.2638 nan 0.0100 -11985667.0979
## 520 40164786378.3987 nan 0.0100 12310681.1468
## 540 39600344358.2806 nan 0.0100 -9939109.0386
## 560 39101911944.0359 nan 0.0100 3496257.2421
## 580 38632920258.7296 nan 0.0100 245212.4148
## 600 38195283008.4304 nan 0.0100 13454562.2767
## 620 37827031572.7730 nan 0.0100 -8917239.2349
## 640 37478231963.2292 nan 0.0100 -4737226.4576
## 660 37084132724.0148 nan 0.0100 7424997.8949
## 680 36716011231.8082 nan 0.0100 -9128534.1432
## 700 36388012028.1158 nan 0.0100 -15103995.3465
## 720 36049595102.7554 nan 0.0100 -11962624.9036
## 740 35772448726.5702 nan 0.0100 -744514.4622
## 760 35474704196.1134 nan 0.0100 490249.7197
## 780 35152514498.9350 nan 0.0100 -10793732.3712
## 800 34887247122.6093 nan 0.0100 -19345155.9610
## 820 34638916554.7221 nan 0.0100 -26861603.5950
## 840 34374060986.5620 nan 0.0100 -35174692.1242
## 860 34091573803.2047 nan 0.0100 -1791098.8192
## 880 33842542253.3830 nan 0.0100 -34687294.5052
## 900 33587459447.1533 nan 0.0100 -10102676.6194
## 920 33355769601.2053 nan 0.0100 -10802966.0622
## 940 33144508893.9000 nan 0.0100 -30351227.8391
## 960 32900126283.8970 nan 0.0100 8165897.0434
## 980 32661115479.7949 nan 0.0100 -4834062.1421
## 1000 32467878213.1099 nan 0.0100 -37391764.3882
## 1020 32195837899.1288 nan 0.0100 594106.6715
## 1040 31970934789.4474 nan 0.0100 -4237752.1983
## 1060 31761337811.3719 nan 0.0100 -6486424.5387
## 1080 31575903277.9263 nan 0.0100 -12454833.4568
## 1100 31383464202.8673 nan 0.0100 -11431869.6365
## 1120 31164334128.8601 nan 0.0100 -7013514.4506
## 1140 31008426269.6623 nan 0.0100 -15325527.6460
## 1160 30776346786.5596 nan 0.0100 -3149456.7820
## 1180 30610753032.6061 nan 0.0100 -1851775.7357
## 1200 30446062274.2750 nan 0.0100 -13821909.4627
## 1220 30307502644.6631 nan 0.0100 -8890537.9530
## 1240 30153121532.6514 nan 0.0100 -11737876.5722
## 1260 29924625618.1618 nan 0.0100 -24856861.5703
## 1280 29775473017.1365 nan 0.0100 -16790964.9127
## 1300 29621324426.3835 nan 0.0100 -32200875.3084
## 1320 29433053202.2873 nan 0.0100 -11794512.5694
## 1340 29275613176.8652 nan 0.0100 -20138062.0244
## 1360 29129225201.6874 nan 0.0100 -26650248.9446
## 1380 28971054260.6727 nan 0.0100 -3384479.7550
## 1400 28844683534.8213 nan 0.0100 -5298024.3022
## 1420 28722907684.5774 nan 0.0100 -10715186.0849
## 1440 28574253840.7683 nan 0.0100 9661349.9812
## 1460 28423223605.4486 nan 0.0100 -6452194.8185
## 1480 28290963325.2020 nan 0.0100 -1878703.5981
## 1500 28146724123.4398 nan 0.0100 -1639825.8116
## 1520 27995471246.5716 nan 0.0100 -4698354.7693
## 1540 27839698856.2750 nan 0.0100 -22157242.6456
## 1560 27676236059.8979 nan 0.0100 -12314509.3056
## 1580 27542999835.6717 nan 0.0100 -16007568.0639
## 1600 27421878902.9562 nan 0.0100 -6610335.6110
## 1620 27323543855.2517 nan 0.0100 -14280393.4820
## 1640 27168300747.5916 nan 0.0100 -5157218.4868
## 1660 27047888892.1665 nan 0.0100 -1262844.1705
## 1680 26940692551.3878 nan 0.0100 -10950032.6553
## 1700 26853558746.0304 nan 0.0100 -7125917.0379
## 1720 26731707280.9983 nan 0.0100 3590376.1450
## 1740 26636669877.4918 nan 0.0100 -8207936.2139
## 1760 26523028969.8496 nan 0.0100 -883897.8911
## 1780 26419099721.9868 nan 0.0100 -8244718.1348
## 1800 26294164591.2500 nan 0.0100 -10679078.5643
## 1820 26205666919.4638 nan 0.0100 -11505272.5228
## 1840 26075669193.7310 nan 0.0100 -8538135.3866
## 1860 26007187203.7704 nan 0.0100 -13728057.6258
## 1880 25898996234.0403 nan 0.0100 -16478925.3587
## 1900 25798638417.9320 nan 0.0100 -2430953.5269
## 1920 25699000779.3323 nan 0.0100 -14796992.9933
## 1940 25593852345.2818 nan 0.0100 -11799923.9676
## 1960 25482011688.6494 nan 0.0100 -12561781.8812
## 1980 25371832309.6431 nan 0.0100 -5262702.1387
## 2000 25271965099.4025 nan 0.0100 -8184042.0236
## 2020 25173445939.7734 nan 0.0100 -3523059.9807
## 2040 25066125533.2160 nan 0.0100 -12595695.9567
## 2060 24966592659.1571 nan 0.0100 -6194152.4526
## 2080 24874579669.3159 nan 0.0100 3702007.4095
## 2100 24784032027.6145 nan 0.0100 -6327110.4706
## 2120 24676177443.7459 nan 0.0100 903890.8648
## 2140 24580622480.3066 nan 0.0100 -8775585.6310
## 2160 24489529660.9664 nan 0.0100 -6393948.9471
## 2180 24412473710.8081 nan 0.0100 -6000057.3285
## 2200 24336145556.8549 nan 0.0100 -10882563.8955
## 2220 24237306906.7079 nan 0.0100 -11624787.1700
## 2240 24152951914.5127 nan 0.0100 -8327879.8885
## 2260 24063319032.1687 nan 0.0100 -10397398.2604
## 2280 23978067671.8439 nan 0.0100 -8571448.7548
## 2300 23895421127.5210 nan 0.0100 -19699532.8963
## 2320 23836184986.5078 nan 0.0100 -11399110.1967
## 2340 23750635780.0698 nan 0.0100 -2562934.7128
## 2360 23659852719.0137 nan 0.0100 -4175122.9863
## 2380 23574805596.4725 nan 0.0100 -11429647.7362
## 2400 23495482362.8699 nan 0.0100 -10792935.5162
## 2420 23409362937.4266 nan 0.0100 -10365008.0823
## 2440 23310059157.2261 nan 0.0100 -6469333.3960
## 2460 23215622487.5246 nan 0.0100 -3689375.9372
## 2480 23141208029.2960 nan 0.0100 -14676460.7352
## 2500 23067944771.5538 nan 0.0100 -5872542.5370
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 266734805156.8680 nan 0.0100 3098768977.9327
## 2 263588152508.8990 nan 0.0100 3031128879.6643
## 3 260167179349.5966 nan 0.0100 3168094137.6232
## 4 257127632926.5656 nan 0.0100 3054693164.9129
## 5 253950104979.7240 nan 0.0100 3381266572.0095
## 6 250695796110.7866 nan 0.0100 3488451403.7372
## 7 247666741483.4153 nan 0.0100 3026256758.6863
## 8 244855268203.4397 nan 0.0100 2938995562.6323
## 9 242025073893.1996 nan 0.0100 2577421191.2725
## 10 239351668392.0664 nan 0.0100 2713881919.4963
## 20 213635559167.8867 nan 0.0100 2392520181.1292
## 40 175487132849.5387 nan 0.0100 1586890034.3338
## 60 147159246524.5957 nan 0.0100 1278068702.6653
## 80 125811307468.7195 nan 0.0100 554600050.8073
## 100 109224291482.3572 nan 0.0100 683305902.2769
## 120 96582018870.2008 nan 0.0100 331406700.8768
## 140 86697483626.2755 nan 0.0100 393062294.5180
## 160 78533050801.0097 nan 0.0100 377642990.9064
## 180 71775605449.6206 nan 0.0100 209000495.6351
## 200 66119468151.0495 nan 0.0100 132428748.9543
## 220 61524566687.9545 nan 0.0100 136647855.2467
## 240 57814078723.9115 nan 0.0100 138104289.9370
## 260 54599576580.8781 nan 0.0100 134493591.6936
## 280 51918902965.7036 nan 0.0100 72122126.1678
## 300 49696076973.5353 nan 0.0100 96107617.4676
## 320 47859320028.4546 nan 0.0100 44556065.0758
## 340 46288819326.6945 nan 0.0100 37367371.2402
## 360 45003167347.4022 nan 0.0100 30776683.8310
## 380 43856813354.0239 nan 0.0100 45321961.2832
## 400 42876015399.1109 nan 0.0100 35294800.7170
## 420 42080660427.7643 nan 0.0100 36842487.8470
## 440 41334087974.0969 nan 0.0100 11945163.8967
## 460 40630388268.0019 nan 0.0100 7610076.0471
## 480 40011525436.4998 nan 0.0100 -10485172.1103
## 500 39501539296.2860 nan 0.0100 -18792199.8527
## 520 38981781908.7719 nan 0.0100 -13997116.7263
## 540 38513242948.3074 nan 0.0100 -4993038.9004
## 560 38073550961.1942 nan 0.0100 -18669157.5180
## 580 37676499912.8503 nan 0.0100 -14297984.0073
## 600 37315177344.0045 nan 0.0100 -6644928.7390
## 620 36945116004.3243 nan 0.0100 -5008716.3104
## 640 36605442383.4789 nan 0.0100 -9469230.9989
## 660 36233156379.1423 nan 0.0100 -14644315.3498
## 680 35897253895.9801 nan 0.0100 -3035372.0826
## 700 35580876213.5999 nan 0.0100 1607480.7470
## 720 35292076033.0802 nan 0.0100 -4966795.1459
## 740 35020600673.3849 nan 0.0100 5967473.1988
## 760 34716031560.3607 nan 0.0100 4364041.6743
## 780 34437618573.6766 nan 0.0100 -437674.4942
## 800 34192562976.4423 nan 0.0100 1607219.2257
## 820 33901918065.0295 nan 0.0100 -22899356.1438
## 840 33618330590.3479 nan 0.0100 -19473539.1058
## 860 33366772327.4417 nan 0.0100 -2405025.2490
## 880 33146823970.5021 nan 0.0100 -12531824.1002
## 900 32903233498.2388 nan 0.0100 -16733863.4821
## 920 32728136294.8823 nan 0.0100 -8055921.2391
## 940 32537985169.4017 nan 0.0100 -7003764.0485
## 960 32273412106.2005 nan 0.0100 -1414190.0837
## 980 32055625210.1096 nan 0.0100 -7693873.4873
## 1000 31798297610.3255 nan 0.0100 -14988560.8720
## 1020 31595398569.4909 nan 0.0100 -14593368.3085
## 1040 31389471968.1027 nan 0.0100 -4089344.3631
## 1060 31210879424.6344 nan 0.0100 -14207895.2505
## 1080 31039381205.0868 nan 0.0100 -417744.2240
## 1100 30863125894.2879 nan 0.0100 -6618802.7782
## 1120 30704474046.5876 nan 0.0100 -5622454.0292
## 1140 30496542107.2777 nan 0.0100 -9335240.1021
## 1160 30297469376.7193 nan 0.0100 -7896398.1638
## 1180 30161686334.8569 nan 0.0100 -13339870.6924
## 1200 29991824242.7708 nan 0.0100 -13571667.8461
## 1220 29839190690.3742 nan 0.0100 -11349956.1333
## 1240 29665483870.8892 nan 0.0100 -5065511.8038
## 1260 29531356677.6621 nan 0.0100 -641297.9036
## 1280 29376876256.2591 nan 0.0100 -18808733.2664
## 1300 29209938406.9097 nan 0.0100 -6747844.4010
## 1320 29073699662.3099 nan 0.0100 -8464556.6544
## 1340 28926668323.3265 nan 0.0100 -4714874.5169
## 1360 28770421600.1955 nan 0.0100 -27098038.7104
## 1380 28615135093.4523 nan 0.0100 -14680620.5084
## 1400 28456723817.9255 nan 0.0100 -10198743.9396
## 1420 28316038479.9669 nan 0.0100 -20425238.6217
## 1440 28176995071.5354 nan 0.0100 -253544.0492
## 1460 28049447152.4108 nan 0.0100 1673166.6656
## 1480 27911393923.5184 nan 0.0100 -2813966.3034
## 1500 27781030397.0143 nan 0.0100 -11678138.8119
## 1520 27664576298.0396 nan 0.0100 -5615067.1855
## 1540 27517732923.9566 nan 0.0100 -10740667.6201
## 1560 27390336224.9692 nan 0.0100 -8469726.5161
## 1580 27247334179.6020 nan 0.0100 -10561612.5215
## 1600 27125448541.3974 nan 0.0100 -20646500.7306
## 1620 27015848253.7455 nan 0.0100 -2484227.0046
## 1640 26911954214.0526 nan 0.0100 -10633104.8822
## 1660 26778272704.2685 nan 0.0100 -13169230.9368
## 1680 26659495394.7438 nan 0.0100 -15359501.0089
## 1700 26553637940.6388 nan 0.0100 -13748563.0856
## 1720 26447262011.0103 nan 0.0100 -1496876.8546
## 1740 26311097609.7532 nan 0.0100 -37778385.5438
## 1760 26208776087.6344 nan 0.0100 -17097058.3657
## 1780 26080004377.6928 nan 0.0100 -730694.3443
## 1800 25986460574.6469 nan 0.0100 -3907050.2117
## 1820 25871227430.4093 nan 0.0100 -4569027.5850
## 1840 25751291014.5183 nan 0.0100 4419282.7183
## 1860 25664419838.1165 nan 0.0100 -15272515.7098
## 1880 25575816223.7553 nan 0.0100 -11039593.6575
## 1900 25450483609.4718 nan 0.0100 -6886251.6730
## 1920 25364632466.2694 nan 0.0100 -10233549.9402
## 1940 25281134177.7691 nan 0.0100 -9697586.7158
## 1960 25203565633.4351 nan 0.0100 -10130601.3688
## 1980 25090257790.4972 nan 0.0100 -62334.7212
## 2000 24986829712.6233 nan 0.0100 -12046132.1238
## 2020 24887239295.0902 nan 0.0100 -11904398.9850
## 2040 24776853208.7767 nan 0.0100 -9521344.6257
## 2060 24649532490.3385 nan 0.0100 -12413831.6128
## 2080 24554388312.8615 nan 0.0100 -5819128.8236
## 2100 24473331812.7169 nan 0.0100 -7957222.9865
## 2120 24379706872.6155 nan 0.0100 -4250161.2780
## 2140 24289833709.3413 nan 0.0100 -5403094.9824
## 2160 24188130026.4802 nan 0.0100 -10149743.9411
## 2180 24089730408.2303 nan 0.0100 -9341550.5925
## 2200 24009055069.2423 nan 0.0100 -11187661.3376
## 2220 23941167608.0164 nan 0.0100 -2738001.1244
## 2240 23846908040.9929 nan 0.0100 1684660.0054
## 2260 23757568934.4863 nan 0.0100 -12819613.4719
## 2280 23684229300.9955 nan 0.0100 -11558281.8588
## 2300 23593457445.1541 nan 0.0100 -2950243.9813
## 2320 23503103269.9380 nan 0.0100 -9407886.1331
## 2340 23422826542.8323 nan 0.0100 -1505793.2919
## 2360 23324953357.0548 nan 0.0100 1780307.1440
## 2380 23257882093.2099 nan 0.0100 -14213620.0551
## 2400 23173989563.5341 nan 0.0100 -6685737.4048
## 2420 23087833857.8379 nan 0.0100 -8059452.3514
## 2440 23003777552.7395 nan 0.0100 -3603869.8159
## 2460 22932125232.9358 nan 0.0100 -13382750.5151
## 2480 22827989498.6088 nan 0.0100 -7710477.1027
## 2500 22746594031.1264 nan 0.0100 -15579101.2688
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 259806451009.6945 nan 0.0100 3194980871.3896
## 2 256899868709.2953 nan 0.0100 3152624830.3410
## 3 253685004164.3614 nan 0.0100 2912895754.1301
## 4 250558234197.2763 nan 0.0100 2653736307.2381
## 5 247524256440.4156 nan 0.0100 2838970253.1534
## 6 244802494700.4324 nan 0.0100 2356627247.1186
## 7 241853030897.5366 nan 0.0100 2738456583.9930
## 8 238987872106.0806 nan 0.0100 2930972518.3508
## 9 236048946872.5959 nan 0.0100 2796696448.7623
## 10 233437592605.2700 nan 0.0100 2514064810.6573
## 20 208832693101.1672 nan 0.0100 2019137654.3238
## 40 171501304699.7964 nan 0.0100 1402518664.5527
## 60 143849711238.5571 nan 0.0100 966910242.2615
## 80 123148087351.2228 nan 0.0100 791764993.8703
## 100 107513183312.6620 nan 0.0100 737297176.6565
## 120 95521710788.7291 nan 0.0100 476845636.5886
## 140 85516039843.4384 nan 0.0100 352888470.4193
## 160 77868500039.8299 nan 0.0100 301726562.6483
## 180 71617774087.3527 nan 0.0100 258041198.3588
## 200 66382408566.1075 nan 0.0100 202975609.8545
## 220 61805988965.9752 nan 0.0100 142975063.4099
## 240 58228475075.1796 nan 0.0100 109634198.2121
## 260 55091999183.3937 nan 0.0100 113867858.3028
## 280 52566217790.5683 nan 0.0100 101454374.7303
## 300 50458240096.2332 nan 0.0100 56148086.2320
## 320 48593102612.6418 nan 0.0100 55830549.6250
## 340 47108409881.0469 nan 0.0100 47142152.7586
## 360 45790952106.8797 nan 0.0100 25009338.9351
## 380 44669655567.8897 nan 0.0100 8537883.2413
## 400 43683058468.2934 nan 0.0100 28401749.2911
## 420 42810698865.9792 nan 0.0100 25371289.9527
## 440 42055099736.1045 nan 0.0100 5491763.8025
## 460 41326614162.3192 nan 0.0100 -3575580.6107
## 480 40712899371.5929 nan 0.0100 17248499.8249
## 500 40161334354.5692 nan 0.0100 9036475.2762
## 520 39683592424.5532 nan 0.0100 21860309.0409
## 540 39198859034.6479 nan 0.0100 3313418.4978
## 560 38763661230.7306 nan 0.0100 -4278198.4726
## 580 38302959347.1514 nan 0.0100 -18696475.0275
## 600 37878744680.9977 nan 0.0100 -36256127.1388
## 620 37510919425.2059 nan 0.0100 9936637.6453
## 640 37158974824.7992 nan 0.0100 -1722302.1212
## 660 36819400149.3608 nan 0.0100 -10438550.9475
## 680 36502227268.5807 nan 0.0100 -11677444.4311
## 700 36217430102.6477 nan 0.0100 2384331.5989
## 720 35849888908.2283 nan 0.0100 -9502824.6285
## 740 35520790873.1307 nan 0.0100 -11947081.9764
## 760 35184688909.9510 nan 0.0100 -20983520.1786
## 780 34908286377.3020 nan 0.0100 -3448138.2330
## 800 34674139991.5376 nan 0.0100 -4753082.7635
## 820 34413803625.4758 nan 0.0100 -963479.9438
## 840 34149641937.7364 nan 0.0100 -45682198.4886
## 860 33889818122.0327 nan 0.0100 -1773391.6729
## 880 33688302526.5521 nan 0.0100 -6256413.3007
## 900 33444967880.8139 nan 0.0100 -16981982.5902
## 920 33202463661.8997 nan 0.0100 -15013352.4382
## 940 33013676000.1763 nan 0.0100 -15278509.2526
## 960 32792061641.8496 nan 0.0100 -16277156.1678
## 980 32578528027.1158 nan 0.0100 -7176338.1550
## 1000 32354292464.3088 nan 0.0100 -4519687.5335
## 1020 32167577558.0406 nan 0.0100 -12240700.6561
## 1040 31986786285.1615 nan 0.0100 -5065478.1489
## 1060 31761343489.3785 nan 0.0100 -15279316.9800
## 1080 31559778602.7493 nan 0.0100 -20532275.2373
## 1100 31383715947.1938 nan 0.0100 -6587905.3962
## 1120 31181000263.7456 nan 0.0100 -12483567.4119
## 1140 31019209555.7107 nan 0.0100 5196409.2862
## 1160 30873344198.2547 nan 0.0100 -6593193.1172
## 1180 30714831180.5550 nan 0.0100 -15059077.0408
## 1200 30575391607.2681 nan 0.0100 -11226976.0204
## 1220 30413616325.0914 nan 0.0100 -11179328.9854
## 1240 30257157801.9850 nan 0.0100 -8223261.1394
## 1260 30085201501.4616 nan 0.0100 -3555533.9292
## 1280 29929764979.2743 nan 0.0100 -15188066.0482
## 1300 29759981778.1398 nan 0.0100 2280475.2015
## 1320 29612168998.2928 nan 0.0100 -451826.6237
## 1340 29475130702.0401 nan 0.0100 -7505185.5933
## 1360 29321625754.5171 nan 0.0100 -7539119.9235
## 1380 29193023095.4075 nan 0.0100 -9848826.5643
## 1400 29058518789.3925 nan 0.0100 1924702.5226
## 1420 28932356848.8299 nan 0.0100 -11406904.0266
## 1440 28797217038.1777 nan 0.0100 -3615514.6048
## 1460 28657107358.2979 nan 0.0100 -17286029.8977
## 1480 28522998987.5457 nan 0.0100 -9870611.5678
## 1500 28399642837.7603 nan 0.0100 -7095493.4849
## 1520 28242494124.9634 nan 0.0100 2955075.8103
## 1540 28091069307.4826 nan 0.0100 -12463459.7919
## 1560 27983760093.9918 nan 0.0100 -10418891.3913
## 1580 27841785872.9623 nan 0.0100 575738.9808
## 1600 27738871067.3911 nan 0.0100 -3685262.6746
## 1620 27618957574.7281 nan 0.0100 -1984664.2926
## 1640 27496197847.2965 nan 0.0100 -11318828.3125
## 1660 27355473291.2109 nan 0.0100 -10688378.6080
## 1680 27243565916.5376 nan 0.0100 -17407038.8282
## 1700 27121438783.8780 nan 0.0100 -11210525.4796
## 1720 27012974800.7779 nan 0.0100 -22382094.5382
## 1740 26889954837.2035 nan 0.0100 -9654924.1471
## 1760 26804101737.9811 nan 0.0100 -6411192.0395
## 1780 26682345045.8015 nan 0.0100 -10351419.2248
## 1800 26550754059.9253 nan 0.0100 -2667385.4157
## 1820 26439425582.8957 nan 0.0100 -7560259.1336
## 1840 26336461058.1305 nan 0.0100 93014.0396
## 1860 26224696111.5353 nan 0.0100 -8610781.5029
## 1880 26097390066.3197 nan 0.0100 -9705338.1767
## 1900 25959287403.6747 nan 0.0100 -6352054.7202
## 1920 25843777874.8921 nan 0.0100 -9105001.6750
## 1940 25738929113.2292 nan 0.0100 -3183270.1798
## 1960 25639356771.5313 nan 0.0100 -1223702.6075
## 1980 25565517551.3137 nan 0.0100 -8213213.4311
## 2000 25449767515.7850 nan 0.0100 -100073.9659
## 2020 25354413617.8430 nan 0.0100 -1207874.1757
## 2040 25270468820.6879 nan 0.0100 -6322550.6528
## 2060 25158707416.5752 nan 0.0100 -4411568.0055
## 2080 25055441894.9655 nan 0.0100 -9719967.1957
## 2100 24928697746.2155 nan 0.0100 -1417114.4115
## 2120 24837386147.5418 nan 0.0100 -3945012.8592
## 2140 24750139034.5298 nan 0.0100 -9829678.7664
## 2160 24645949439.5921 nan 0.0100 -4717235.7263
## 2180 24572582484.7396 nan 0.0100 -11549911.4662
## 2200 24479818292.9548 nan 0.0100 -5853499.6489
## 2220 24395203257.7131 nan 0.0100 -4916162.1969
## 2240 24307184359.1492 nan 0.0100 -401615.9280
## 2260 24209356997.9410 nan 0.0100 -6895077.8814
## 2280 24117924461.1967 nan 0.0100 -1783702.2617
## 2300 24030643385.5270 nan 0.0100 -4697768.9500
## 2320 23939639078.3964 nan 0.0100 -3554238.5210
## 2340 23843432730.1745 nan 0.0100 -6329800.9100
## 2360 23761354298.6206 nan 0.0100 -2324501.9738
## 2380 23685615937.0391 nan 0.0100 -2403680.9779
## 2400 23597999152.7532 nan 0.0100 -11111570.3489
## 2420 23524743620.2239 nan 0.0100 -6071664.6407
## 2440 23453410415.8592 nan 0.0100 -3845040.6380
## 2460 23372877282.1768 nan 0.0100 -3624776.1235
## 2480 23295647620.8509 nan 0.0100 -3520733.8227
## 2500 23224821343.4099 nan 0.0100 -18077177.2079model6_stacking <- caretStack(
modelList,
method = "glm", #we use logistic regression as a combiner algorithm to balance between underlying models
metric = "RMSE",
trControl = stackingControl
)
stackingPredictions <- predict(model6_stacking,test_data)
stacking_results<-data.frame(RMSE = RMSE(stackingPredictions, test_data$price),
Rsquare = R2(stackingPredictions, test_data$price))
stacking_results## RMSE Rsquare
## 1 179790 0.8910761As we can see, this one-time oos testing has given us a slighlty worse performance than support vector machines. However, it is likely to assume that across different tests, stacking will be more consistent and robust due to mitigated overfitting.
#lets look at the confidence intervals for RMSEs of each underlying model
resamples <- resamples(modelList)
dotplot(resamples, metric = "RMSE")
modelCor(resamples)## svm ranger gbm
## svm 1.0000000 0.9493160 0.9007801
## ranger 0.9493160 1.0000000 0.8410876
## gbm 0.9007801 0.8410876 1.0000000The above plot aids in determining the robustness of our out of sample performance result. As we can see, the width of each confidence interval across the underlying algorithms are rather similar. This hints at a well balanced choice of models for the ensemble algorithm. As a next step, lets assess what happens when we include linear regression in the stacking algorithm. Maybe this has the potential to enhance the final result, since it might counteract the tendency to overfit of the existing three models.
withLRmodelList <- caretList(
price ~ total_floor_area + district + london_zone + number_habitable_rooms + co2_emissions_potential + distance_to_station +water_company+property_type+latitude+ longitude + average_income + property_type,
train_data,
trControl = stackingControl,
tuneList = list(
lr = caretModelSpec(method = "lm"),
svm = caretModelSpec(method = "svmRadial", tuneGrid = data.frame(sigma = 0.01226624 , C = 32)),
ranger = caretModelSpec(method = "ranger", tuneGrid = data.frame(mtry=47,splitrule="extratrees",min.node.size=5)),
gbm = caretModelSpec(method = "gbm", tuneGrid = data.frame(n.trees = 2500, interaction.depth = 5, shrinkage = 0.01, n.minobsinnode = 10))
))## Warning in trControlCheck(x = trControl, y = target): trControl$savePredictions
## not 'all' or 'final'. Setting to 'final' so we can ensemble the models.## Warning in trControlCheck(x = trControl, y = target): indexes not defined in
## trControl. Attempting to set them ourselves, so each model in the ensemble will
## have the same resampling indexes.## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 261146400749.2632 nan 0.0100 2719654125.2215
## 2 258116603742.0698 nan 0.0100 2961818085.0608
## 3 255033662209.4858 nan 0.0100 2516050793.2005
## 4 251973240832.1237 nan 0.0100 2800096262.7776
## 5 248881349831.2318 nan 0.0100 3173276362.3472
## 6 246001167728.9142 nan 0.0100 2727677484.1194
## 7 242964194354.0497 nan 0.0100 3055399523.1015
## 8 240066698232.5309 nan 0.0100 3135784720.5744
## 9 237276548502.7657 nan 0.0100 2723694345.3740
## 10 234503990409.3590 nan 0.0100 2796727221.8514
## 20 209842898756.7293 nan 0.0100 2284695220.7232
## 40 170578528921.5523 nan 0.0100 1759773337.0192
## 60 143098200200.1042 nan 0.0100 1069838266.8362
## 80 122292337453.6307 nan 0.0100 819874374.3528
## 100 106675844343.0493 nan 0.0100 645893576.3157
## 120 94503377047.0660 nan 0.0100 538776934.7629
## 140 84744032402.3247 nan 0.0100 416502014.5962
## 160 77104146142.0732 nan 0.0100 342923559.9560
## 180 70650709344.0132 nan 0.0100 244340759.3289
## 200 65526075366.3568 nan 0.0100 177744997.8801
## 220 61190616564.2085 nan 0.0100 157791231.4938
## 240 57589950347.7964 nan 0.0100 104431364.2191
## 260 54577986384.3337 nan 0.0100 76620490.0787
## 280 52079748784.0608 nan 0.0100 75431816.5482
## 300 50053552465.6879 nan 0.0100 84958467.0668
## 320 48215597832.3507 nan 0.0100 67359629.4678
## 340 46667533833.5311 nan 0.0100 79520703.5235
## 360 45346027767.1589 nan 0.0100 25796693.3553
## 380 44273917139.7645 nan 0.0100 -9231504.3797
## 400 43288899600.6183 nan 0.0100 22925158.5301
## 420 42379009671.9344 nan 0.0100 27649792.5653
## 440 41593546774.1805 nan 0.0100 1303451.3678
## 460 40882336643.8138 nan 0.0100 5079765.1330
## 480 40223801549.7679 nan 0.0100 15842889.9875
## 500 39571611889.4044 nan 0.0100 -17560517.5187
## 520 39053343418.2536 nan 0.0100 -1708499.2723
## 540 38588194026.5715 nan 0.0100 -6945862.8936
## 560 38129965478.4622 nan 0.0100 9960970.0698
## 580 37672001072.0182 nan 0.0100 17937508.1231
## 600 37249001137.2982 nan 0.0100 -2035847.9610
## 620 36816082187.6836 nan 0.0100 4570325.0409
## 640 36430739934.5053 nan 0.0100 18298427.0889
## 660 36042771708.5370 nan 0.0100 -5633981.3250
## 680 35707150414.8979 nan 0.0100 -15700505.2922
## 700 35385263952.0064 nan 0.0100 -2893376.7603
## 720 35082369431.6731 nan 0.0100 -17016175.8908
## 740 34783464180.3864 nan 0.0100 -5661765.4631
## 760 34489325553.6426 nan 0.0100 1612442.9341
## 780 34218788367.8881 nan 0.0100 -30284259.5883
## 800 33961894574.0761 nan 0.0100 2113293.6674
## 820 33708794782.2470 nan 0.0100 -1779748.6865
## 840 33440245323.1339 nan 0.0100 -5748423.4535
## 860 33130046650.7327 nan 0.0100 -6298669.8851
## 880 32860085931.9108 nan 0.0100 -16110356.3776
## 900 32638953621.5396 nan 0.0100 -7813375.4663
## 920 32440640961.2353 nan 0.0100 -6082055.4026
## 940 32187965795.5575 nan 0.0100 -8091089.1592
## 960 31955889024.8129 nan 0.0100 -12009355.9919
## 980 31771587082.9202 nan 0.0100 175390.2206
## 1000 31559274676.7659 nan 0.0100 -4812590.0934
## 1020 31317401763.5128 nan 0.0100 -9931591.0370
## 1040 31137063568.4473 nan 0.0100 -3578377.3199
## 1060 30964934331.9009 nan 0.0100 -7507128.0598
## 1080 30771733374.2730 nan 0.0100 -12952815.9265
## 1100 30561206886.5194 nan 0.0100 -26700506.2658
## 1120 30359765909.2126 nan 0.0100 495884.2489
## 1140 30155186691.7140 nan 0.0100 -377938.7305
## 1160 29966801751.0490 nan 0.0100 -9169387.2670
## 1180 29776627464.4235 nan 0.0100 -23718940.0877
## 1200 29596081298.2679 nan 0.0100 -10142651.4765
## 1220 29424008176.2708 nan 0.0100 -19237129.8817
## 1240 29268086953.4990 nan 0.0100 -3252613.5780
## 1260 29108503607.9748 nan 0.0100 -14417092.2958
## 1280 28977572346.0856 nan 0.0100 -5496634.0499
## 1300 28814856914.7230 nan 0.0100 -7410858.7090
## 1320 28673002498.8308 nan 0.0100 -11532120.1625
## 1340 28530130905.9860 nan 0.0100 -24973735.9359
## 1360 28375526376.1647 nan 0.0100 3006098.1638
## 1380 28237718335.1136 nan 0.0100 -4598502.1743
## 1400 28105420071.9438 nan 0.0100 -8381406.4296
## 1420 27991098286.0961 nan 0.0100 -7630881.2674
## 1440 27872382131.8133 nan 0.0100 -16795331.8746
## 1460 27738529163.8645 nan 0.0100 -12666961.1178
## 1480 27623394453.0098 nan 0.0100 -12032780.2287
## 1500 27478570395.4325 nan 0.0100 -21345120.0033
## 1520 27363075546.8068 nan 0.0100 -10404457.9706
## 1540 27244025709.6465 nan 0.0100 -5542143.9664
## 1560 27135672341.8752 nan 0.0100 -1390850.0418
## 1580 27020672720.0084 nan 0.0100 -4576839.4514
## 1600 26883095970.9125 nan 0.0100 -5997563.1840
## 1620 26753503674.9550 nan 0.0100 -3149265.4844
## 1640 26640336898.0113 nan 0.0100 -5800828.7648
## 1660 26521888076.0183 nan 0.0100 -14873574.3349
## 1680 26393120809.6404 nan 0.0100 -16591692.3431
## 1700 26256297992.1260 nan 0.0100 -3883182.4729
## 1720 26142959678.6850 nan 0.0100 -8623184.5275
## 1740 26019714221.0748 nan 0.0100 -7377503.2904
## 1760 25894179764.1510 nan 0.0100 -2488749.3440
## 1780 25780742259.0285 nan 0.0100 -7291486.4120
## 1800 25682123106.5923 nan 0.0100 -5745262.8594
## 1820 25551448102.5257 nan 0.0100 -9617339.5940
## 1840 25418519729.9950 nan 0.0100 -4986046.5072
## 1860 25318775539.6874 nan 0.0100 -2056279.0909
## 1880 25207321074.6317 nan 0.0100 -1695835.6973
## 1900 25121023027.8432 nan 0.0100 -8325671.3555
## 1920 25021010901.2587 nan 0.0100 -7501665.5797
## 1940 24909633330.5570 nan 0.0100 -12002706.4061
## 1960 24795767866.8480 nan 0.0100 -10784318.9235
## 1980 24695482089.8994 nan 0.0100 -4197681.4399
## 2000 24581039085.4852 nan 0.0100 -6020922.3139
## 2020 24492419305.0240 nan 0.0100 -8941966.3119
## 2040 24389175643.3750 nan 0.0100 -11324477.4281
## 2060 24294604276.3337 nan 0.0100 -3961445.6811
## 2080 24199710094.1501 nan 0.0100 -4746610.7416
## 2100 24092880694.8961 nan 0.0100 878844.4892
## 2120 23989004568.9913 nan 0.0100 -7880385.5075
## 2140 23900616275.8173 nan 0.0100 -2311186.5099
## 2160 23802965072.2531 nan 0.0100 -12129420.4616
## 2180 23714158715.3976 nan 0.0100 -9708799.1298
## 2200 23626519179.7855 nan 0.0100 -7890231.1803
## 2220 23543738340.0331 nan 0.0100 -6466139.7467
## 2240 23460640492.1521 nan 0.0100 1298065.5145
## 2260 23354794925.9533 nan 0.0100 -3016108.1167
## 2280 23269874323.4097 nan 0.0100 -1396901.4662
## 2300 23183741046.0040 nan 0.0100 -7035658.9139
## 2320 23072475836.7475 nan 0.0100 -10040130.1149
## 2340 22999315274.1432 nan 0.0100 -1720412.9270
## 2360 22928658351.3272 nan 0.0100 -9775730.6647
## 2380 22843082994.2847 nan 0.0100 -5724842.5353
## 2400 22756999562.0608 nan 0.0100 -994812.3946
## 2420 22675620627.8980 nan 0.0100 -5416619.5267
## 2440 22594200254.7556 nan 0.0100 -3772751.2228
## 2460 22482088516.8614 nan 0.0100 -5404574.9712
## 2480 22400147748.7770 nan 0.0100 -5764818.5657
## 2500 22322421994.0839 nan 0.0100 -8549563.6354
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 260885574590.0043 nan 0.0100 3027354427.0961
## 2 257763986073.7538 nan 0.0100 2863368160.3701
## 3 254905923252.2024 nan 0.0100 2981294032.4308
## 4 251667144778.2764 nan 0.0100 3032036934.7087
## 5 248869401014.8211 nan 0.0100 3079629219.4331
## 6 246049687077.3229 nan 0.0100 2575782950.9830
## 7 243221119250.3181 nan 0.0100 2620160750.3183
## 8 240351965894.4690 nan 0.0100 2559198210.6118
## 9 237500774143.0041 nan 0.0100 3180034109.1265
## 10 234773641259.9056 nan 0.0100 2546472602.6697
## 20 210314873127.2405 nan 0.0100 2329520362.7358
## 40 172496014018.5316 nan 0.0100 1817165878.7500
## 60 143862332938.0987 nan 0.0100 1085344732.4446
## 80 122631929962.5768 nan 0.0100 850124944.5063
## 100 106553970074.8297 nan 0.0100 617085317.8094
## 120 94105890441.9355 nan 0.0100 505699936.9253
## 140 84139005429.2370 nan 0.0100 364614826.0569
## 160 76060141164.5728 nan 0.0100 288181569.3863
## 180 69583088703.2540 nan 0.0100 178670727.3072
## 200 64270843502.1537 nan 0.0100 153163380.5195
## 220 59781874315.9306 nan 0.0100 154231053.3005
## 240 56072469193.7330 nan 0.0100 134387627.3740
## 260 52944350261.4610 nan 0.0100 76902910.4123
## 280 50387111972.4163 nan 0.0100 83555062.0096
## 300 48158935408.6931 nan 0.0100 62695363.1547
## 320 46394125871.7758 nan 0.0100 79328165.6414
## 340 44861675906.0403 nan 0.0100 75433257.8551
## 360 43595157977.5727 nan 0.0100 37308862.6289
## 380 42456402255.4773 nan 0.0100 51288544.5241
## 400 41525666637.1715 nan 0.0100 32925268.8290
## 420 40660192253.8910 nan 0.0100 2175419.6573
## 440 39842250886.7349 nan 0.0100 -4530937.6366
## 460 39192164832.7792 nan 0.0100 -4628713.3077
## 480 38532263164.0416 nan 0.0100 -151939.7046
## 500 37968709463.4732 nan 0.0100 3372986.5344
## 520 37421791134.4849 nan 0.0100 -8914401.3242
## 540 36941290815.5146 nan 0.0100 3792917.9162
## 560 36425098204.0906 nan 0.0100 1207556.8022
## 580 36032178448.8356 nan 0.0100 -14983275.9615
## 600 35633395577.7022 nan 0.0100 -2825501.9858
## 620 35199550829.0956 nan 0.0100 12601942.6466
## 640 34782932855.4808 nan 0.0100 -23271403.9357
## 660 34420005014.8766 nan 0.0100 3133593.9159
## 680 34074746141.3831 nan 0.0100 -11939764.0530
## 700 33747574805.7756 nan 0.0100 -33355020.4392
## 720 33492055186.4869 nan 0.0100 465882.3382
## 740 33192744043.7816 nan 0.0100 8115244.4562
## 760 32899952245.5390 nan 0.0100 -17672301.5346
## 780 32620448501.8859 nan 0.0100 -17182599.1598
## 800 32340841653.5413 nan 0.0100 -11080369.0306
## 820 32051420018.9867 nan 0.0100 -32490527.8801
## 840 31787136518.7918 nan 0.0100 3732475.6708
## 860 31546450485.0234 nan 0.0100 1673070.4340
## 880 31318185229.6215 nan 0.0100 -9415248.4258
## 900 31085419711.8758 nan 0.0100 -37135935.4157
## 920 30821757224.5915 nan 0.0100 -23446909.5394
## 940 30591415268.0580 nan 0.0100 -6897051.3370
## 960 30374353620.0951 nan 0.0100 -19768300.8218
## 980 30131776730.8947 nan 0.0100 -11996251.3749
## 1000 29881654991.9028 nan 0.0100 -5766718.4452
## 1020 29663598058.2237 nan 0.0100 -386583.9115
## 1040 29488750402.9144 nan 0.0100 -18206119.4155
## 1060 29281282159.8087 nan 0.0100 -3105130.5804
## 1080 29065219362.9229 nan 0.0100 -11845562.6666
## 1100 28878375310.4176 nan 0.0100 -18122639.1015
## 1120 28693533192.4129 nan 0.0100 168891.1950
## 1140 28494292524.4599 nan 0.0100 -13605544.5844
## 1160 28329923896.9299 nan 0.0100 -15646348.9533
## 1180 28169268751.5044 nan 0.0100 -11393580.3513
## 1200 27994608746.8155 nan 0.0100 -11597407.8931
## 1220 27840748067.2953 nan 0.0100 -12317848.5795
## 1240 27695787537.1007 nan 0.0100 -3134366.8761
## 1260 27541106804.8381 nan 0.0100 -8659164.0719
## 1280 27399104920.8993 nan 0.0100 -5241705.8315
## 1300 27238119374.8109 nan 0.0100 -16400612.6668
## 1320 27102675095.4476 nan 0.0100 -6981175.8799
## 1340 26945539020.5602 nan 0.0100 -11257290.1309
## 1360 26809142577.6934 nan 0.0100 -5452716.0568
## 1380 26654421625.4705 nan 0.0100 -4719633.7355
## 1400 26512448961.7997 nan 0.0100 -7119289.3607
## 1420 26388224890.8209 nan 0.0100 -10207064.9518
## 1440 26227918842.4932 nan 0.0100 1474430.9731
## 1460 26080855654.5864 nan 0.0100 -13516650.2839
## 1480 25919067451.3006 nan 0.0100 -160892.2813
## 1500 25771418689.0286 nan 0.0100 -14864315.7082
## 1520 25643225885.3270 nan 0.0100 -3103688.2814
## 1540 25469962304.8642 nan 0.0100 -2280556.1949
## 1560 25339085225.4628 nan 0.0100 -10037792.4312
## 1580 25237814864.7708 nan 0.0100 -9957878.4511
## 1600 25103131966.7114 nan 0.0100 3876552.4667
## 1620 24977689242.8474 nan 0.0100 -6855444.3725
## 1640 24848396835.0889 nan 0.0100 -9233773.6855
## 1660 24723423557.9322 nan 0.0100 -13820884.0114
## 1680 24619865078.4550 nan 0.0100 -12179578.4233
## 1700 24504455194.6388 nan 0.0100 -12559263.7908
## 1720 24378476484.5396 nan 0.0100 -1534725.5722
## 1740 24245062352.0667 nan 0.0100 1550907.4416
## 1760 24135303440.5488 nan 0.0100 -8075085.3055
## 1780 24026085606.3913 nan 0.0100 -12934218.9540
## 1800 23922924248.6337 nan 0.0100 -7873454.1702
## 1820 23819723814.7111 nan 0.0100 -11936441.0692
## 1840 23716951326.3541 nan 0.0100 -3398088.0832
## 1860 23624372757.9115 nan 0.0100 -7670590.3635
## 1880 23507936901.3163 nan 0.0100 -15191117.7289
## 1900 23395221771.4650 nan 0.0100 -7667138.4549
## 1920 23286457113.7346 nan 0.0100 -5506248.0627
## 1940 23173534136.1531 nan 0.0100 -15230094.1868
## 1960 23069946250.5674 nan 0.0100 -2717196.7959
## 1980 22978117704.2300 nan 0.0100 -504347.2035
## 2000 22868253433.1545 nan 0.0100 -6699038.8633
## 2020 22776758694.6915 nan 0.0100 -930658.1192
## 2040 22670795482.8676 nan 0.0100 -11742041.7335
## 2060 22587988510.0505 nan 0.0100 -14112860.7905
## 2080 22498995189.7439 nan 0.0100 -6478159.9916
## 2100 22418854463.9230 nan 0.0100 -16926840.4831
## 2120 22306277913.0733 nan 0.0100 386782.2521
## 2140 22225425223.5383 nan 0.0100 -13343960.5282
## 2160 22125812152.6160 nan 0.0100 -10086185.3069
## 2180 22033551237.9245 nan 0.0100 -10481423.1269
## 2200 21960340167.3656 nan 0.0100 -7858982.1952
## 2220 21875480285.0330 nan 0.0100 -1057661.1379
## 2240 21773850408.5264 nan 0.0100 -8267501.1535
## 2260 21676838357.9251 nan 0.0100 -10801500.2893
## 2280 21576797352.4952 nan 0.0100 -1710768.3694
## 2300 21503019477.9304 nan 0.0100 -7578681.2228
## 2320 21431631549.0919 nan 0.0100 -6076977.6490
## 2340 21347545675.1825 nan 0.0100 -9178875.1556
## 2360 21267260624.9646 nan 0.0100 -6678680.2483
## 2380 21194991579.9964 nan 0.0100 -8517948.4893
## 2400 21110597835.6448 nan 0.0100 1275824.9859
## 2420 21031284874.5059 nan 0.0100 -5860599.7818
## 2440 20949575657.0308 nan 0.0100 -10932124.5825
## 2460 20868787172.7653 nan 0.0100 -4353500.7962
## 2480 20792953468.4935 nan 0.0100 -8901604.5709
## 2500 20721214706.4559 nan 0.0100 -6878550.8203
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 274539156879.5850 nan 0.0100 3147406620.3159
## 2 271295575606.5973 nan 0.0100 2658335778.2388
## 3 267827481087.1486 nan 0.0100 3233520505.4577
## 4 264497004665.7226 nan 0.0100 3641726556.0823
## 5 261169639412.6839 nan 0.0100 3204288221.0019
## 6 258162242148.7434 nan 0.0100 3170098715.9337
## 7 255371018021.9863 nan 0.0100 2539577134.2033
## 8 252543087524.0085 nan 0.0100 2435567147.6456
## 9 249493183937.9458 nan 0.0100 3081883659.0206
## 10 246509198615.9378 nan 0.0100 3104399732.5913
## 20 220492984247.6124 nan 0.0100 2246963383.1623
## 40 179618017914.2563 nan 0.0100 1510042603.7756
## 60 149743846760.9365 nan 0.0100 1204141258.7427
## 80 127432780812.9130 nan 0.0100 849597102.5110
## 100 110463993278.7775 nan 0.0100 628406468.7983
## 120 97237040149.8408 nan 0.0100 592620833.4515
## 140 86807922990.9180 nan 0.0100 424547762.5803
## 160 78403786426.6312 nan 0.0100 287879664.1576
## 180 71440586753.8459 nan 0.0100 158188303.5144
## 200 65709302843.5960 nan 0.0100 205655835.5803
## 220 61138686548.8148 nan 0.0100 212667946.7134
## 240 57419905715.8873 nan 0.0100 161272296.6209
## 260 54331136267.9959 nan 0.0100 111173551.7940
## 280 51787260038.5807 nan 0.0100 59016212.0537
## 300 49534625447.4378 nan 0.0100 81090411.0875
## 320 47533211566.6340 nan 0.0100 76599435.6872
## 340 45970525721.5475 nan 0.0100 60207908.5026
## 360 44623500499.3810 nan 0.0100 39425280.5477
## 380 43410724162.5231 nan 0.0100 28608833.4826
## 400 42367810643.1935 nan 0.0100 -11470996.9565
## 420 41500626584.1190 nan 0.0100 17124838.6822
## 440 40697467194.2430 nan 0.0100 16457704.6214
## 460 39990005990.7546 nan 0.0100 9530586.3725
## 480 39412575116.0200 nan 0.0100 14630008.5971
## 500 38852454584.5691 nan 0.0100 -17634589.3347
## 520 38365037158.2397 nan 0.0100 -7867501.5763
## 540 37853890706.4511 nan 0.0100 6217782.4680
## 560 37447329491.3853 nan 0.0100 -2059480.9327
## 580 36989903726.6418 nan 0.0100 -33233225.4979
## 600 36573772600.8284 nan 0.0100 12740648.4609
## 620 36214639137.2013 nan 0.0100 2421770.1859
## 640 35819931907.6587 nan 0.0100 -44330277.6388
## 660 35447919008.1167 nan 0.0100 -11016978.1927
## 680 35125917589.4861 nan 0.0100 -22241382.9681
## 700 34775437930.5877 nan 0.0100 -9583553.7294
## 720 34461371561.1895 nan 0.0100 -7373373.0888
## 740 34190800437.4294 nan 0.0100 -5677673.8091
## 760 33903471823.7530 nan 0.0100 -11664101.0844
## 780 33557473313.0033 nan 0.0100 -3010112.9891
## 800 33266971875.9511 nan 0.0100 -14531108.9388
## 820 33000514760.6143 nan 0.0100 -17182445.4466
## 840 32753814098.5981 nan 0.0100 -6713544.4373
## 860 32527893526.7739 nan 0.0100 -20226052.4810
## 880 32271296683.7746 nan 0.0100 -16184906.9080
## 900 32023382445.1166 nan 0.0100 -35045854.7799
## 920 31792135188.2573 nan 0.0100 -9151648.1177
## 940 31556284545.1042 nan 0.0100 -30132696.9560
## 960 31376346901.3561 nan 0.0100 -5220441.6102
## 980 31116060439.5208 nan 0.0100 -4037215.6611
## 1000 30902233732.8126 nan 0.0100 -29013699.3299
## 1020 30717154475.7284 nan 0.0100 -7277952.6294
## 1040 30518274375.1308 nan 0.0100 -8170287.0519
## 1060 30335862747.1407 nan 0.0100 -15574446.9722
## 1080 30104772231.2076 nan 0.0100 -10859360.7308
## 1100 29881931657.3416 nan 0.0100 -7584445.3750
## 1120 29630887975.4511 nan 0.0100 -4028374.1141
## 1140 29415929482.2847 nan 0.0100 1439855.2017
## 1160 29228234653.7677 nan 0.0100 -23451077.7253
## 1180 29056690375.4576 nan 0.0100 -19438292.7785
## 1200 28923747449.5913 nan 0.0100 -18875341.4713
## 1220 28743811369.6085 nan 0.0100 -16746997.4991
## 1240 28570672931.8655 nan 0.0100 -3750332.0728
## 1260 28421993478.7295 nan 0.0100 -15867467.3555
## 1280 28226734717.3176 nan 0.0100 -22028927.8264
## 1300 28033729522.6115 nan 0.0100 3932876.7390
## 1320 27888415376.9266 nan 0.0100 -7835289.3683
## 1340 27736351122.0126 nan 0.0100 -3700261.4737
## 1360 27597105734.5328 nan 0.0100 4216113.2696
## 1380 27457622697.4459 nan 0.0100 -6498512.2852
## 1400 27307110767.6377 nan 0.0100 -12969802.4196
## 1420 27170830168.2351 nan 0.0100 -6699886.8629
## 1440 27022929558.3111 nan 0.0100 -6055291.6426
## 1460 26852878502.6973 nan 0.0100 -1895214.4470
## 1480 26699969173.0851 nan 0.0100 -10544302.4106
## 1500 26586801318.4278 nan 0.0100 -14626476.4303
## 1520 26467792405.3152 nan 0.0100 -7404660.3214
## 1540 26312176776.3080 nan 0.0100 -13813029.9918
## 1560 26200924827.9128 nan 0.0100 -11038822.7661
## 1580 26076260401.0306 nan 0.0100 -8962096.2761
## 1600 25947786215.7955 nan 0.0100 -9835148.2096
## 1620 25816373237.3703 nan 0.0100 -5562086.7730
## 1640 25700381638.9965 nan 0.0100 -6641512.4055
## 1660 25586740732.5984 nan 0.0100 -4284249.7047
## 1680 25460800464.5507 nan 0.0100 -1347369.8940
## 1700 25339575926.0955 nan 0.0100 -4339978.6553
## 1720 25216990129.8183 nan 0.0100 -14683596.8726
## 1740 25102055025.0825 nan 0.0100 -2947958.3692
## 1760 24991578679.2482 nan 0.0100 -14052734.1934
## 1780 24839225905.8732 nan 0.0100 -8556175.9294
## 1800 24729492934.1031 nan 0.0100 -8845232.8696
## 1820 24634458253.4743 nan 0.0100 -11119285.0513
## 1840 24551216571.8856 nan 0.0100 -3505675.6981
## 1860 24451273752.8234 nan 0.0100 -2180825.5827
## 1880 24346459758.4227 nan 0.0100 -5383236.4805
## 1900 24239048291.4497 nan 0.0100 -8081814.0415
## 1920 24134562202.1164 nan 0.0100 -2717264.6151
## 1940 24040355727.1267 nan 0.0100 -9953648.7708
## 1960 23935917305.1996 nan 0.0100 -1066987.9656
## 1980 23818479639.1549 nan 0.0100 -8554313.0819
## 2000 23732532872.0263 nan 0.0100 2022351.1048
## 2020 23608508442.8760 nan 0.0100 27006.0191
## 2040 23524999561.7909 nan 0.0100 -6296993.8626
## 2060 23430482753.9822 nan 0.0100 -4808512.3490
## 2080 23329393898.1072 nan 0.0100 -3585773.1188
## 2100 23243813745.3760 nan 0.0100 -2626735.6965
## 2120 23136943544.8317 nan 0.0100 -11621111.4776
## 2140 23052665225.1435 nan 0.0100 -7034677.0622
## 2160 22967431663.5924 nan 0.0100 -485716.2836
## 2180 22881608046.2357 nan 0.0100 -2724238.5469
## 2200 22793324783.1414 nan 0.0100 -9097161.9565
## 2220 22694290468.2701 nan 0.0100 -6325239.7364
## 2240 22610430369.4128 nan 0.0100 -7027127.9811
## 2260 22517536110.7086 nan 0.0100 1199854.3273
## 2280 22433422229.0217 nan 0.0100 -7176657.1887
## 2300 22351873587.0753 nan 0.0100 -7526128.0860
## 2320 22270714632.5773 nan 0.0100 -3056696.7027
## 2340 22173573372.6205 nan 0.0100 -4904543.2121
## 2360 22085944296.1288 nan 0.0100 -846335.2887
## 2380 22004939093.1630 nan 0.0100 1399199.7185
## 2400 21933045970.0280 nan 0.0100 -7608323.9664
## 2420 21830105913.9508 nan 0.0100 -6030064.6006
## 2440 21776323482.7909 nan 0.0100 -5025968.0567
## 2460 21709971108.4323 nan 0.0100 -2291574.7571
## 2480 21641191022.6400 nan 0.0100 -5648116.3932
## 2500 21560018389.9997 nan 0.0100 -7335153.3789
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 246919488844.5694 nan 0.0100 2540342272.4754
## 2 244018270164.9123 nan 0.0100 2648326654.4429
## 3 241360552904.4719 nan 0.0100 2710955582.6661
## 4 238580346797.0403 nan 0.0100 2740115273.9918
## 5 235895293584.8377 nan 0.0100 2767057511.6048
## 6 233127487536.9294 nan 0.0100 3009965087.4334
## 7 230445078346.3560 nan 0.0100 2511201245.9264
## 8 227892900092.9455 nan 0.0100 2334004657.6267
## 9 225387656836.0886 nan 0.0100 2309010671.0378
## 10 222958089863.7961 nan 0.0100 2316954725.4743
## 20 200628836600.5950 nan 0.0100 1943793731.0561
## 40 164494983750.2669 nan 0.0100 1476911233.1996
## 60 137678101006.9067 nan 0.0100 1103486344.0938
## 80 117971858891.2227 nan 0.0100 697798424.6333
## 100 102992725526.1609 nan 0.0100 526488462.7486
## 120 91251836073.3963 nan 0.0100 406157661.2012
## 140 81991507441.3022 nan 0.0100 352875401.8854
## 160 74373311527.6918 nan 0.0100 255850016.4531
## 180 68213607369.3075 nan 0.0100 246899508.7877
## 200 63033274291.0310 nan 0.0100 182782482.3489
## 220 58768165259.1938 nan 0.0100 86215582.3971
## 240 55257637894.2189 nan 0.0100 86525185.1158
## 260 52344731708.2122 nan 0.0100 56670613.9265
## 280 50002540628.0448 nan 0.0100 76948922.5116
## 300 47935151913.4660 nan 0.0100 77924199.6219
## 320 46233700114.9474 nan 0.0100 66496719.8624
## 340 44744203426.4876 nan 0.0100 51020237.4513
## 360 43413514739.2737 nan 0.0100 4438227.3709
## 380 42296536766.5182 nan 0.0100 39496960.5032
## 400 41286303749.4635 nan 0.0100 45716076.1242
## 420 40380527348.8539 nan 0.0100 -4623307.8842
## 440 39570475980.4775 nan 0.0100 15953613.6565
## 460 38883512598.6898 nan 0.0100 16148956.2786
## 480 38260127453.2783 nan 0.0100 12464924.8891
## 500 37733922199.7931 nan 0.0100 -7511132.1694
## 520 37254702458.0366 nan 0.0100 18149618.7232
## 540 36775108318.1288 nan 0.0100 -1495633.9522
## 560 36376636545.2857 nan 0.0100 -3322094.2793
## 580 36010323705.6001 nan 0.0100 3626087.6428
## 600 35649581016.0657 nan 0.0100 12549400.6909
## 620 35265954113.9994 nan 0.0100 -25905429.0654
## 640 34918667204.4388 nan 0.0100 -2371275.0278
## 660 34624920324.1082 nan 0.0100 -14636300.2368
## 680 34351839645.4720 nan 0.0100 1603302.2232
## 700 34071200693.8613 nan 0.0100 -38404667.6163
## 720 33755494050.3983 nan 0.0100 1799083.0844
## 740 33425609142.9416 nan 0.0100 -12126728.6944
## 760 33187443018.9810 nan 0.0100 -25841286.0883
## 780 32935308444.9112 nan 0.0100 -42190290.9196
## 800 32679663691.4272 nan 0.0100 -7863440.4396
## 820 32417277913.8998 nan 0.0100 -15147136.5908
## 840 32170864517.0937 nan 0.0100 -13474564.6182
## 860 31958576738.4219 nan 0.0100 9330119.7543
## 880 31763656694.1109 nan 0.0100 -8084908.0555
## 900 31549664590.4211 nan 0.0100 2395886.7076
## 920 31351806244.2673 nan 0.0100 -9558955.3037
## 940 31116208936.8008 nan 0.0100 -2403540.2953
## 960 30926340712.5070 nan 0.0100 -11869715.6088
## 980 30731584856.3887 nan 0.0100 -6989088.0660
## 1000 30546373596.9483 nan 0.0100 2553909.2542
## 1020 30327836226.8004 nan 0.0100 5759859.9615
## 1040 30150545217.4548 nan 0.0100 -9869071.3366
## 1060 29983687283.5332 nan 0.0100 203495.0296
## 1080 29806991414.2776 nan 0.0100 -10993495.7950
## 1100 29647843241.7609 nan 0.0100 -28097422.6734
## 1120 29470548547.5375 nan 0.0100 2892716.7203
## 1140 29331167577.8287 nan 0.0100 4463793.6354
## 1160 29197831889.4661 nan 0.0100 -7885152.7749
## 1180 29030209244.5633 nan 0.0100 -9793586.4411
## 1200 28859290163.1358 nan 0.0100 -14631697.6544
## 1220 28708413675.4039 nan 0.0100 535606.6873
## 1240 28570754611.3924 nan 0.0100 -17107933.5798
## 1260 28432554398.2592 nan 0.0100 -4983263.1201
## 1280 28292474619.3827 nan 0.0100 -12010873.7374
## 1300 28156884422.7942 nan 0.0100 -6518685.2793
## 1320 28009933239.7877 nan 0.0100 -10587217.7941
## 1340 27893990723.7332 nan 0.0100 -13816658.9860
## 1360 27747450908.3687 nan 0.0100 -9518488.8696
## 1380 27621870842.1573 nan 0.0100 -2301218.7681
## 1400 27513470123.8812 nan 0.0100 -11837991.2850
## 1420 27366326836.7355 nan 0.0100 -11948920.2346
## 1440 27239523411.9562 nan 0.0100 -11321201.4977
## 1460 27091583612.2386 nan 0.0100 -7177879.8529
## 1480 26944297258.9958 nan 0.0100 -6567308.2806
## 1500 26806358092.8983 nan 0.0100 -4556351.1659
## 1520 26678908024.6674 nan 0.0100 -8486813.7834
## 1540 26546009101.1175 nan 0.0100 -17025798.3480
## 1560 26447266564.2705 nan 0.0100 -3504287.8726
## 1580 26322481111.8768 nan 0.0100 -14528355.9145
## 1600 26203838797.0282 nan 0.0100 -4723647.2520
## 1620 26091067866.6426 nan 0.0100 -10141615.9558
## 1640 25966519265.5722 nan 0.0100 -8447445.3884
## 1660 25844967199.3130 nan 0.0100 860383.3347
## 1680 25735213556.7105 nan 0.0100 -5673099.5779
## 1700 25623465058.5064 nan 0.0100 -7226211.8035
## 1720 25518675912.0151 nan 0.0100 -19668249.5834
## 1740 25413116516.6135 nan 0.0100 -13720538.5101
## 1760 25312287658.8051 nan 0.0100 -10204243.0061
## 1780 25180012251.1682 nan 0.0100 -2012344.3257
## 1800 25089652346.9355 nan 0.0100 -6065141.3911
## 1820 24962804505.9617 nan 0.0100 -7117405.1227
## 1840 24878558935.2035 nan 0.0100 -6894377.9164
## 1860 24789116732.1101 nan 0.0100 -10466494.5295
## 1880 24682326135.3631 nan 0.0100 -6697400.4162
## 1900 24587108373.5553 nan 0.0100 -7057204.2268
## 1920 24502392617.2280 nan 0.0100 -2570533.2609
## 1940 24409289335.1598 nan 0.0100 -10325190.4020
## 1960 24333563987.6749 nan 0.0100 -11623493.4769
## 1980 24238323470.2172 nan 0.0100 -9426076.4019
## 2000 24149854718.7000 nan 0.0100 -3295756.9573
## 2020 24040394241.3597 nan 0.0100 -2344856.2967
## 2040 23944988999.3696 nan 0.0100 -2007480.6171
## 2060 23831682970.0549 nan 0.0100 -9277563.5315
## 2080 23733807628.3365 nan 0.0100 -10393596.3797
## 2100 23671402700.9330 nan 0.0100 -7065536.7937
## 2120 23579858953.4034 nan 0.0100 -7827777.0426
## 2140 23495872578.6549 nan 0.0100 -8919528.6269
## 2160 23397833640.1094 nan 0.0100 -2864523.8998
## 2180 23335317755.2750 nan 0.0100 -16256593.6903
## 2200 23256190413.3910 nan 0.0100 -8411734.5979
## 2220 23167226189.1636 nan 0.0100 -7117823.8699
## 2240 23087386343.3447 nan 0.0100 -5574081.9615
## 2260 23006044212.7898 nan 0.0100 -8388353.2820
## 2280 22937213958.0142 nan 0.0100 -7446814.7707
## 2300 22838729860.2655 nan 0.0100 -6251241.4929
## 2320 22748246116.1588 nan 0.0100 -16052142.0302
## 2340 22656308910.8816 nan 0.0100 -4197420.4610
## 2360 22562410042.7689 nan 0.0100 -5765460.1178
## 2380 22484506884.7534 nan 0.0100 -9312538.7331
## 2400 22403191239.5232 nan 0.0100 -5573320.4017
## 2420 22330459757.7416 nan 0.0100 -1530034.5051
## 2440 22267237432.6207 nan 0.0100 -9785861.4157
## 2460 22192540468.1497 nan 0.0100 -356986.1933
## 2480 22120763339.9219 nan 0.0100 -7627251.3438
## 2500 22051683905.4421 nan 0.0100 -9518745.2845
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 254204934524.8964 nan 0.0100 2758900331.1020
## 2 251430591953.5809 nan 0.0100 2919650811.2854
## 3 248497072910.1058 nan 0.0100 2841103777.4150
## 4 245684408004.2096 nan 0.0100 2705436187.3503
## 5 242894364664.4059 nan 0.0100 2636435581.4206
## 6 240134863172.0498 nan 0.0100 2336171750.9665
## 7 237500427789.8011 nan 0.0100 2661204130.2903
## 8 234848978877.9509 nan 0.0100 2252902748.7899
## 9 232334431705.1811 nan 0.0100 2299563390.8155
## 10 229773431536.5082 nan 0.0100 2653149354.1734
## 20 206848303403.2672 nan 0.0100 1994070755.8598
## 40 171197240152.8062 nan 0.0100 1500404093.0311
## 60 144569792174.6614 nan 0.0100 967436728.0982
## 80 124531745102.6213 nan 0.0100 888079067.2917
## 100 109159189946.7774 nan 0.0100 575208293.9684
## 120 96789583146.6898 nan 0.0100 449592818.1900
## 140 87341750975.7349 nan 0.0100 450791367.0652
## 160 79579154267.6243 nan 0.0100 314306204.2245
## 180 73122911476.4632 nan 0.0100 259995294.2676
## 200 67875781342.3662 nan 0.0100 181274385.6285
## 220 63494587299.3417 nan 0.0100 184402645.9056
## 240 59821296059.0071 nan 0.0100 93993089.7834
## 260 56742118870.3438 nan 0.0100 70808553.4716
## 280 54342023617.4592 nan 0.0100 135830997.7218
## 300 52142359069.9244 nan 0.0100 87565107.9564
## 320 50277167487.9892 nan 0.0100 42327386.9489
## 340 48670283997.5072 nan 0.0100 2757667.6950
## 360 47382906386.6802 nan 0.0100 38342276.6063
## 380 46207103329.0505 nan 0.0100 19805730.8232
## 400 45230501732.4012 nan 0.0100 14624944.6960
## 420 44330192358.6965 nan 0.0100 18978925.0661
## 440 43544820409.1875 nan 0.0100 -15529950.8972
## 460 42780899120.1870 nan 0.0100 9764392.6223
## 480 42178464762.3128 nan 0.0100 16423020.3429
## 500 41597174499.7469 nan 0.0100 19668116.6894
## 520 41046466049.1935 nan 0.0100 -16951747.5569
## 540 40542416283.1469 nan 0.0100 -9014518.0533
## 560 40124876681.9903 nan 0.0100 -23452279.1579
## 580 39674761900.3615 nan 0.0100 -1610387.3493
## 600 39236558413.4669 nan 0.0100 1568726.9893
## 620 38849963283.9963 nan 0.0100 -34536294.4208
## 640 38503586988.8772 nan 0.0100 -2149249.4148
## 660 38177453001.5930 nan 0.0100 2101928.5194
## 680 37857367618.2530 nan 0.0100 12887000.1058
## 700 37466888444.2497 nan 0.0100 2513400.6547
## 720 37104378515.0903 nan 0.0100 14404434.0997
## 740 36771253532.5041 nan 0.0100 7680415.6220
## 760 36467824869.6645 nan 0.0100 -5101545.7477
## 780 36191940804.6758 nan 0.0100 -17909188.8239
## 800 35920601468.8588 nan 0.0100 1220557.8437
## 820 35662956316.3710 nan 0.0100 -16809777.6722
## 840 35381622491.1171 nan 0.0100 -1004956.4664
## 860 35151854402.5648 nan 0.0100 -13277011.2206
## 880 34878234823.2401 nan 0.0100 -24519388.8231
## 900 34621067496.0873 nan 0.0100 -8260639.0998
## 920 34369261956.0571 nan 0.0100 -15422856.9644
## 940 34119841223.6989 nan 0.0100 3259638.7856
## 960 33892005515.2430 nan 0.0100 -22330375.1782
## 980 33657757468.0893 nan 0.0100 -37572165.4711
## 1000 33438159808.4130 nan 0.0100 767392.6288
## 1020 33216806403.8465 nan 0.0100 -20010744.6427
## 1040 33025340927.4485 nan 0.0100 4436823.5151
## 1060 32829023786.8827 nan 0.0100 -2474871.0133
## 1080 32594598677.0092 nan 0.0100 -10194910.3957
## 1100 32410209119.2863 nan 0.0100 -15640870.3550
## 1120 32192492588.6459 nan 0.0100 -20300980.4556
## 1140 31985010341.7179 nan 0.0100 -2575431.7884
## 1160 31769982695.1307 nan 0.0100 -16208356.2295
## 1180 31602532253.0455 nan 0.0100 -6360034.9855
## 1200 31431568045.4826 nan 0.0100 -6511961.9651
## 1220 31270459858.3488 nan 0.0100 -16255812.9144
## 1240 31096432617.7794 nan 0.0100 -13759234.0223
## 1260 30921769591.7302 nan 0.0100 -13559219.8550
## 1280 30748946019.2953 nan 0.0100 -35756208.4761
## 1300 30562399926.8411 nan 0.0100 -6331930.5727
## 1320 30395496176.1547 nan 0.0100 3861869.1427
## 1340 30232266988.4591 nan 0.0100 486694.2342
## 1360 30057413206.9042 nan 0.0100 -22550709.2562
## 1380 29915162278.5707 nan 0.0100 356158.9868
## 1400 29746725252.8479 nan 0.0100 -3400500.4892
## 1420 29612345590.1077 nan 0.0100 908263.9226
## 1440 29471680017.6226 nan 0.0100 -1743192.2866
## 1460 29308767429.7206 nan 0.0100 -6570060.7762
## 1480 29190773371.1631 nan 0.0100 -17527149.3707
## 1500 29018755809.4802 nan 0.0100 -20326594.6750
## 1520 28880961053.3449 nan 0.0100 -7032799.9770
## 1540 28758696897.1510 nan 0.0100 -11677938.3586
## 1560 28645806457.7688 nan 0.0100 -27405343.5901
## 1580 28483128436.5346 nan 0.0100 -4227245.7210
## 1600 28361423891.6568 nan 0.0100 -11219472.0417
## 1620 28211713690.8788 nan 0.0100 -11570899.1538
## 1640 28106517734.1524 nan 0.0100 -7875535.4862
## 1660 27976918034.2840 nan 0.0100 -1266446.5612
## 1680 27854650101.1113 nan 0.0100 4240139.8011
## 1700 27728083122.4017 nan 0.0100 -17664869.0613
## 1720 27597621711.5844 nan 0.0100 1530206.7812
## 1740 27446419720.5603 nan 0.0100 -12938610.9076
## 1760 27319739522.5172 nan 0.0100 -14603180.4637
## 1780 27193452722.3548 nan 0.0100 -6776881.9302
## 1800 27076576638.0114 nan 0.0100 -22965447.3910
## 1820 26940227234.6881 nan 0.0100 -9220967.6874
## 1840 26824427138.1578 nan 0.0100 -5452233.6301
## 1860 26719691414.5523 nan 0.0100 -9563867.2203
## 1880 26618455259.8427 nan 0.0100 2375423.3574
## 1900 26505457567.5214 nan 0.0100 -11236010.3321
## 1920 26373564516.5190 nan 0.0100 -4920628.7948
## 1940 26261240519.0165 nan 0.0100 -3132291.8904
## 1960 26151146648.0288 nan 0.0100 -10166504.9284
## 1980 26033059709.6750 nan 0.0100 -15341819.5622
## 2000 25937776899.1207 nan 0.0100 -3626364.9790
## 2020 25834955732.2796 nan 0.0100 -9989492.7058
## 2040 25730850500.5920 nan 0.0100 -8539684.6481
## 2060 25627486286.0758 nan 0.0100 -6280942.5227
## 2080 25543008362.4286 nan 0.0100 -2322681.3350
## 2100 25439523092.6101 nan 0.0100 -2334684.4768
## 2120 25346786262.8129 nan 0.0100 -14156003.4118
## 2140 25252538965.4966 nan 0.0100 -7499358.3938
## 2160 25147366702.5003 nan 0.0100 -4600635.9762
## 2180 25057023311.9995 nan 0.0100 -11632015.6598
## 2200 24955755416.8649 nan 0.0100 -6785023.7166
## 2220 24866009778.4043 nan 0.0100 -3959901.8875
## 2240 24768389209.2774 nan 0.0100 -12067891.7427
## 2260 24670451294.3818 nan 0.0100 -4331474.6564
## 2280 24568974392.9667 nan 0.0100 -11904931.0223
## 2300 24454860622.1227 nan 0.0100 -2068988.7090
## 2320 24369053907.5234 nan 0.0100 -8437869.6109
## 2340 24267789896.2779 nan 0.0100 -6993395.3139
## 2360 24163049044.7121 nan 0.0100 -9308618.3058
## 2380 24075447457.8864 nan 0.0100 -1808172.9385
## 2400 23998689415.8196 nan 0.0100 -2930442.0850
## 2420 23920696249.8848 nan 0.0100 -18410214.0592
## 2440 23840748513.2374 nan 0.0100 -342957.9807
## 2460 23765108468.8648 nan 0.0100 -9853344.1703
## 2480 23683379267.7833 nan 0.0100 -2331709.1363
## 2500 23604229126.5916 nan 0.0100 -9171045.1723
##
## Iter TrainDeviance ValidDeviance StepSize Improve
## 1 259668304269.4687 nan 0.0100 2919193359.1055
## 2 256746677897.6683 nan 0.0100 3160083912.1106
## 3 253787047957.5468 nan 0.0100 2806042605.6348
## 4 250734295036.9688 nan 0.0100 2611803293.3916
## 5 247842162338.2740 nan 0.0100 2779550730.1367
## 6 244956823023.5443 nan 0.0100 3059688619.9865
## 7 241982208137.1724 nan 0.0100 2764292659.2360
## 8 239158729050.3451 nan 0.0100 2628644686.2962
## 9 236607318161.9515 nan 0.0100 2491581550.2663
## 10 233872162165.9385 nan 0.0100 2491433013.3470
## 20 209655180817.7034 nan 0.0100 1844634867.0362
## 40 172009965272.4497 nan 0.0100 1737345846.2505
## 60 144198852513.5590 nan 0.0100 1167504533.9525
## 80 123624551295.7356 nan 0.0100 886956527.3023
## 100 107651545928.4147 nan 0.0100 617322210.0602
## 120 95409488633.4028 nan 0.0100 545040657.6419
## 140 85640669535.8007 nan 0.0100 389075486.0385
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## 1840 26420648781.1535 nan 0.0100 -12228280.8825
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## 2020 25535947161.6087 nan 0.0100 -6365835.1062
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## 2060 25351269061.5292 nan 0.0100 4065864.5159
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## 2140 24964801555.8835 nan 0.0100 -10756152.1714
## 2160 24883988628.6389 nan 0.0100 -3414618.9818
## 2180 24801703706.7748 nan 0.0100 -8416932.7418
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## 2260 24471040723.7112 nan 0.0100 -1415749.3777
## 2280 24366046830.4915 nan 0.0100 -368714.5537
## 2300 24269286212.5713 nan 0.0100 -7060896.4793
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## 2340 24103572974.9105 nan 0.0100 -10669181.7882
## 2360 24040131737.0275 nan 0.0100 -3012014.1611
## 2380 23959400868.0622 nan 0.0100 -1006599.7250
## 2400 23884307219.4730 nan 0.0100 -13616356.0906
## 2420 23780173103.8059 nan 0.0100 -9028509.2755
## 2440 23710945163.6203 nan 0.0100 -1603920.9093
## 2460 23629443798.9429 nan 0.0100 -2556684.5322
## 2480 23544800398.5466 nan 0.0100 -9138390.7292
## 2500 23469036255.8721 nan 0.0100 -2546444.6104withLRmodel7_stacking <- caretStack(
withLRmodelList,
method = "glm",
metric = "RMSE",
trControl = stackingControl
)
withLRstackingPredictions <- predict(withLRmodel7_stacking,test_data)
withLRstacking_results<-data.frame(RMSE = RMSE(withLRstackingPredictions, test_data$price),
Rsquare = R2(withLRstackingPredictions, test_data$price))
withLRstacking_results## RMSE Rsquare
## 1 181850.1 0.8888764As we can see, the introduction of linear regression to our stacking ensemble actually reduces the out of sample performance slightly. Lets not consider it for our final model.
8 Pick investments
We want to maximiize the average percentage return/profit on invested houses. This means that we have to predict actual prices/valuations as accurately as possible. We thus choose the stacking model (excluding Linear Regression) as it was showing the best out of sample performance.
oos<-london_house_prices_2019_out_of_sample
#predict the value of houses
oos$predict <- predict(model6_stacking,oos)
#Choose the ones you want to invest here
#Make sure you choose exactly 200 of them
mutOos <- oos %>%
mutate(absProfit = predict - asking_price, roi = (predict - asking_price)/asking_price)
#output your choices. Change the name of the file to your "lastname_firstname.csv"
write.csv(mutOos,"my_submission.csv")